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so with that we're going to transition
into uh one of the most exciting pieces

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of content from my perspective for this
conference and that is the thing that

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we've all been discussing for two years
now and it is culminating with an actual

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Peak at the
findings um this was a third-party

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investigation of your cares and ARA
stimulus funds experience

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that Matt burn bound's office committed
to and it was because we heard from all

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of you over the last few years at
conferences that that would be helpful

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so last year Emily Plum and Frank ran
the session on this topic she is right

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here she's going to present later I'm
going to introduce her a little more

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later but uh like a good relay race she
handed the Baton over here to Lisa

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Heckman who is coming to this conference
in person for the first time we're so

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excited to have her here
yay um she's here with Clifton MC

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Reynolds also part of the research and
evaluation

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team we're sort of giving them the
afternoon they have all the content this

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afternoon because they are our
co-sponsors of this conference and they

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enjoy working with you as much as we do
and a lot of this is very pertinent to

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our Collective work but just about Lisa
I want to say that um she has put so

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much thought
and Care into how to present this to you

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in an engaging way um because her report
much like the 30 page regulatory updates

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handout I mean it is a massive report
that she had to distill down into this

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45 minute um preview of highlights and
she did it in a visually engaging way so

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I think you're going to love it Lisa
also just has such a can do Spirit at

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our agency that we appreciate so much
like um this one is not deterred by any

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challenges she just forges ahead and
you're going to see that in evidence

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here so it is my great pleasure to turn
the mic over to

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Lisa thank you so much Terry and thank
you all for having me here it's really

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nice to see everybody in

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person let's see um
oh okay there we go um so just to give

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us all a little context on today's
presentation um as many of you strongly

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remember and many of you have heard um
in 2020 and in 2021 imls distributed

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funds to slas from two pandemic response
and relief efforts the Corona virus Aid

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relief and Economic Security Act or
cares Act and the American Rescue plan

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or
arpa slaa expended over $200 million

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across these two Grant programs um and
just a few numbers again for context um

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for the car's act slaa expended around
$30 million and arpa was even bigger at

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$171 million um that's about five or six
times the cares act funding and um

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notably all of this was on top of all
the work that you all normally do um as

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you can see um these funds resulted in a
huge number of projects which we'll

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contextualize a little bit later and a
huge number of sub Awards and so this is

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all just to speak to the magnitude of
the work that you all

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conducted for this evaluation um we
conducted uh three types of data

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collection we conducted a semi-structure

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oh let's go
back okay thank you

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all righty so we conducted
semi-structured interviews which

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consisted of interviews with all the
grants to State's program officers we

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also invited slaa representatives to
participate in our interviews and we're

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able to reach 34 of you so thank you um
for giving us all your input it was

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really valuable and it's the core of
this

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report we also conducted some
quantitative data analysis using records

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from is imlss State program report
system or spr and finally we conducted a

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literature review to see what was
already published on the topics that we

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were studying um And to clarify the
interview content is all Anonymous and

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um so if you see a reference that says
one state or seven states did this

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that's from the interview data um we are
calling out some really nice

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illustrative examples from the
literature riew or spr where that is

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public information so if you see
anything cited by name that's from

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public um and your interviews um I just
wanted to reassure you that your data

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has been kept
private

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thanks a little bit of background on the
funding reach which was quite impressive

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across the two programs funding reached
more than 40,000 libraries more than 350

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museums and more than 80 tribal
institutions and a made over 9,000 sub

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Awards throughout the presentation I'm
going to be contextualizing this data by

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comparing the cares act in arpa funding
to a benchmark year which is

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2019 um that's to give us the Baseline
to compare our numbers and so in The

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Benchmark here we can see that SLA
expended around

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153 or $154
million um car's Act was smaller than a

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baseline layer but on top of a Bas years
so still a very large stimulus and then

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arpa as I said before was six times that
um and so an even larger um

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investment next I'd like to just cover
funding use again to set the

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scene so thinking about projects that um
that libraries and slas conducted um

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each project has a focal area um that
you ceriz the project within Um this can

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be institutional capacity information
access lifelong learning Civic

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engagement employment and economic
development and Human

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Services this graph shows the percentage
of projects in the cares act arpa and a

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benchmark 2019 year so you can see where
funds tended to go in each of the years

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so these gray diagonally SL bars of The
Benchmark year and you can see that um

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in a benchmark year 2019 about a third a
third and a third um of projects were uh

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focused on uh institutional capacity
information access and lifun learning

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and I think what's striking about the
cares and arpa data uh cares is depicted

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in green on on the left bar leftmost bar
of each of these and and arpa is

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detected in blue in the middle bars what
you can see is there's this big jump in

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the percent percentage of projects that
were um marked as institutional capacity

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and a little bit of a decrease in
information access and lifelong learning

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and of course those were still two of
the bigger areas that projects were

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focused on but um what was really
interesting to us was this institutional

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capacity bump and so the next slide
explains

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that so um Beyond projects um sorry
Beyond Focus areas an spr you also uh

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cat cized projects by the intent which
is like a suble Lev um there's 14

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intents and they each Nest under a focal
um uh

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sorry um they each Nest under a focal
area and so we were really interested

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and since we saw that institutional
capacity jump we wanted to see where

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that came from and the focal areas help
us drill down into institutional

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capacity and say oh what is it about
institutional capacity that projects

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were focused on and what we see here um
looking at The Benchmark The Gray Line

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versus the blue and the um green lines
the biggest jump in intent was um

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improving library's physical and
Technology infrastructure so that was

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about 10% of projects in The Benchmark
year and between 42 and 46 for the kazon

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ARA program so that's a huge increase um
and a lot of that can be explained I

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think by procurements this is one of the
um intent areas where this is the one

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intent area where you'd be able to enter
procurements and as you'll be seeing in

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later slides there was quite a bit of
procurment many of you know that um so

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uh digital access and technology and
Wi-Fi were big areas of purchase um

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physical safety measures were big areas
of purchase in terms of physical um

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infrastructure um there are certain
allowable ways to help improve safety

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that would fall under um this category
and so that was the big um increase and

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then the next thing I want to do is just
show you all the intents there are 14 um

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and give you an idea of what changed in
those covid stimulus um programs versus

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The Benchmark
year so um the way this is ordered is

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from the biggest increases in covid
programs to the small to the biggest de

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decreases during po covid programs so a
positive number means there was a lot

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more projects um aimed at that intent
for kis and arpa and a negative number

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means that there were a lot fewer
percent of projects um in that intent

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during kisan arpa versus this Benchmark
year and so like we showed you before

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the biggest jump um the biggest boost
was in improving libraries physical and

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Technology infrastructure and the
biggest declines were in improving the

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library Workforce improving users
General Knowledge and Skills s and

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improve users abilities to discover
information resources and I think

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another interesting thing is that there
are a lot of sort of zeros and negative

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ones not huge changes um but these kind
of reflect the changing situation and

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changing priorities in that time and of
course this is separate from the normal

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2020 and 2021 uh funds so you still had
all your other activities going but this

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is how cares and arpa funds um tended to
be used

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so um one of my slides didn't show up
but in the evaluation there are sort of

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four topic areas we talked about Co
needs goals and impacts like what were

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libraries and slas trying to achieve and
what did the funding do the next thing

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we talked about was sustainability of um
we the next thing we researched was

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sustainability of funding efforts so
what happened after the funding

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stopped another question that we were
trying to answer in this evaluation was

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about equitable distribution of funding
um how was that achieved was that

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achieved and then the last um topic that
we're covering is Lessons Learned so

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this is the first

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topic obviously as the pandemic
progressed um there were different

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conditions and different cor different
different corresponding needs uh to

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um uh arising from those conditions so
in the earliest phases of the pandemic

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mic there were questions about the
safety of using physical materials and

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obviously widespread Library closures
and so key needs that we heard in our

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interviews included but are not limited
to transferring program to Virtual

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formats digitizing Collections and
developing digital

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products later on in the pandemic um we
saw reduced closures and we also saw

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libraries recognizing the necessity of
all the virtual elements that they had

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you know um started up in the beginning
of the pandemic but also trying to sort

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of adapt to more of a hybrid and more
reintegrated reopening approach and so

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um what we saw in terms of needs from
the interview was providing virtual

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resources still and um providing
increased access to those resources um

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increasing the safety of in-person
operations and providing um numerous

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services such as outdoor and Community
focused programming um to adapt to the

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new times and new

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needs digital access was a a huge topic
that came up in your interview so I

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wanted to spend a second on that one um
slas prioritized increasing access to

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broadband internet and internet
connected Technologies um the result of

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this is that um libraries are able to
purchase laptops for Community residents

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to check out so they could um access
education employment communication um

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health and even recreation
resources libraries also focused on

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improving access to the internet through
hotspots and parking lot Wi-Fi

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um and this sh chart just shows um the
sort of magnitude of purchasing Wi-Fi

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hotspots um in the cares act and arpa
and also other technology like laptops

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and tablets and you can see a really big
spike in arpa on spending on other

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technology
um I'm seeing that like every other

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slide is seems to be
missing um

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but um I I'll just speak to the side
that I think should be there um the side

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that I think should be there is on
physical safety um so physical safety

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measures were also um sorry

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maybe

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not I'll go with whatever slides are
here um moving on to funding impacts um

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we were really interested in sort of
what came out of uh the

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funding so um some great examples came
out of this digital access and digital

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inclusion um topic um these are two uh
examples that I believe came from the

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spr system um the Connecticut State
library for example um distributed

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laptops and hotspots to several
different libraries and um some just

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encouraging quotes came up in the
reporting um for example students

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earning their High School diplomas
because they were able to use this

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technology um obviously with um digital
access um they could uh file for

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unemployment benefits and access
unemployment service assistance as well

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and arrange things like teleah Health
and Medical

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Services um the Carolina State Library
also um had a sort of a digital

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inclusion type programming as well um
and I thought it was really neat to read

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that for students um finished their
studies with the help of uh these

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resources and also even graduated from
Nursing

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School uh mobile services came up as
another big theme um in our um

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research we found that libraries
expanded their use of mobile services

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increasing their reach and bringing
Library services to vulnerable

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populations across their
communities um this was especially true

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in the arpa phase of the pandemic um we
saw that mobile services increased

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during cares but really especially
increased during arpa um and so mobile

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services included um ways to deliver
books to patrons who were unable to

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travel to their Library um there was a
great example of a mobile van with Wi-Fi

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hotspots and laptops for check out and
even a mobile van with Library staff to

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help with homework and job applications
resumés and

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more a question we had were what were
some new and expanded um opportunities

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that arose um during the pandemic one
thing that came up in interviews was

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that uh at first libraries thought of
their modified Services as temporary

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solutions but ended up finding Val value
in them and continued many modified

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Services they also started using well I
shouldn't say started they expanded um

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using their physical space to benefit
the community they've always been hubs

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um places of resources for communities
but um new I think this became even

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greater during the pandemic for example
having a health clinic at your library

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or having an outdoor yoga class at your
library or um building sort of like

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stations where people could have private
tele Health appointments um that uh was

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something that uh folks talked to us a
lot about in the

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interviews and then of course mobile
services as I mentioned was another

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theme um that came out as um a new and
expand well expanded opportunity at this

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time new Partnerships was I thought one
of the really interesting um areas that

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slaa spoke to in their interviews every
single SLA that we talked to described

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working with state and local government
agencies and nonprofit organizations to

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provide unprecedented support for their
states so these Partnerships focused on

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a number of areas anything from
unemployment to education to health and

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there were some creative Partnerships I
have examples on this slide like um

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procuring alcohol-based hand sanitizer
from a

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Distillery and I think that one um
reason uh the Partnerships were quite

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interesting is that a lot of slas
reported that they started some of these

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Partnerships during the pandemic but
maintain them

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afterwards slaa also reported a number
of new practices for themselves so slas

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relied on Virtual meetings more often
especially during the beginning the

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pandemic when there were changing rules
and regulations and health information

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um slas were working to get those
messages out to the libraries in their

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states and so they were able to do so
virtually um to get information out

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rapidly
slaa has reported having continued using

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virtual communication methods which also
means that there are some accessibility

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benefits um now that they able to
um more easily work virtually and in

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hybrid
mode several slas also um reported

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implementing um diversity Equity
accessibility and inclusion and other

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virtual training for their staff and
they also reported that libraries had

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similar trainings

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um yeah and I do think I my slides are
kind of skipping but we're going to

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have uh pause for questions
here so I am going to call up my um

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colleague Emily pman Frank and um we
would like to just hear about what

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questions you may have so far

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um I want to

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congratulations awesome

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expect

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I guess it's kind of surprising than the
3033 pre pandemic I would have known

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that yeah and you know um Clifton's
actually going to be speaking to more

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Trends in that area um and what was
really interesting for me is like we

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used 2019 as a baseline year um just to
say this is before the pandemic things

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were more normal then um but I was
always curious like what is happening in

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the Years Around It is it the best
Baseline year and Clifton will be able

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to speak to that a little bit more and I
think that's a fascinating um sort of

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fascinating finding as well so thanks
thanks for

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asking did you happen to see any um
increase in digital branches in your

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00:21:56.640 --> 00:22:04.240
data uh sorry did you see any increase
in digital branches um I would have to

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ask my um data team to dig in more
that's a great question I'm guessing the

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answer is yes um but I don't
specifically have that data here s

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thanks I was just bringing that up
because um that's something that uh we

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did at our library trle County Public
Library in Kentucky is we already had a

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digital library in place which that was
very cool because um when the pandemic

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AIT and our local libraries did not have
any access to Internet or computers for

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kids we had kids going to um these
digital branches around the county that

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so they could do their school work so I
was just interesting yeah interested to

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see if that's if other states are doing
that can can if anyone would like to

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00:22:46.960 --> 00:22:51.080
know fresher show show hands if like you
heard about your States doing that I'm

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just curious if you'd like to answer um
you all are the experts on what your

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states did

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sure

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yeah and I think one of the slides that
I had that I don't think came up was on

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um digital Navigators was one of the big
findings we were also seeing which again

256
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is not surprising to you while you all
told us this so I am repeating back out

257
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what you told us um but digital
Navigators um came up as a service that

258
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um folks either hired or hired
subscriptions for in order to get people

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00:23:53.600 --> 00:23:58.080
access to the devices they need to um be
connected and also how to use those

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devices and access resources and that
came up just in a number of interviews

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00:24:02.600 --> 00:24:05.480
um so oh

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00:24:08.039 --> 00:24:15.799
please I was wondering if you could
provide a few more examples to

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the yeah um I would have to go back to
the paper for more specific examples so

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00:24:23.320 --> 00:24:27.880
we may want to put it in the parking lot
but one thing that's coming to mind is

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um one Library um set up like a outdoor
bench with like places you could plug in

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your laptops
um I I'm not the best at categorizing

267
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exactly what counts as infrastructure
versus construction versus other things

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um but that might be one of them um
there were things like um creating

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barriers within um the library to create
physical distancing and safety and

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00:24:55.919 --> 00:25:01.559
plexiglass again um that physical in
infrastructure category is a little bit

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fuzzy for me and um but I'm happy to go
to our data team and dig in um because

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that's a great question thank

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00:25:11.399 --> 00:25:15.600
you thanks Emily

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00:25:32.360 --> 00:25:37.000
thanks Emily yeah thank you thank

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you so the next topic we wanted to talk
about was

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sustainability of this funding so once
the funding went out the door and it was

277
00:25:48.960 --> 00:25:54.840
expended what happened
after in our interviews we asked about

278
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activities that um were implemented
during the pandemic what activities have

279
00:25:59.520 --> 00:26:03.880
ended or been reduced which have
continued and which should continue but

280
00:26:03.880 --> 00:26:09.039
would need more funding in order to
continue in terms of ending the one

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00:26:09.039 --> 00:26:13.000
thing we heard the most was PPE and
safety equipment distribution of of

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course that may have not 100% ended but
it it was it's dramatically reduced

283
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compared to the times we were living in
a few years

284
00:26:21.600 --> 00:26:27.919
ago in terms of redu reductions um WiFi
hotspot and database subscriptions were

285
00:26:27.919 --> 00:26:32.880
sometimes reduced due to their cost um
some states and libraries found ways to

286
00:26:32.880 --> 00:26:38.080
continue these things um some had to
reduce them so um what you'll see is

287
00:26:38.080 --> 00:26:42.320
that a lot of the things that fall in
the have reduced column ended up in the

288
00:26:42.320 --> 00:26:45.880
need more funding some people were able
to continue and some would need more

289
00:26:45.880 --> 00:26:51.279
funding to do so and then virtual
outdoor and Community focused

290
00:26:51.279 --> 00:26:56.760
programming still um exists and still
and and you know much of the valuable

291
00:26:56.760 --> 00:27:01.840
programming um was maintained but
anything that required um more funding

292
00:27:01.840 --> 00:27:07.520
or more Staffing could sometimes be at
risk for um being reduced based on those

293
00:27:07.520 --> 00:27:12.640
constraints I think the most interesting
column in this in this uh chart is what

294
00:27:12.640 --> 00:27:16.399
activities have continued so hybrid
programming obviously there were some

295
00:27:16.399 --> 00:27:20.520
setup costs to figure out zoom and
computers and how to broadcast things

296
00:27:20.520 --> 00:27:25.919
but once um once all that hardware and
technology and knowhow um was in place

297
00:27:25.919 --> 00:27:29.720
um many libraries and even the slas um
moved to hyperd

298
00:27:29.720 --> 00:27:33.520
programming equipment that was purchased
like laptops and tablets which was a

299
00:27:33.520 --> 00:27:39.039
huge area of purchase um those purchases
continue to be used but of course at

300
00:27:39.039 --> 00:27:42.799
some point technology um can become
outdated and so there would of course

301
00:27:42.799 --> 00:27:48.559
need to be consideration at that point
of more funding could be

302
00:27:48.559 --> 00:27:53.240
needed um and then um community- based
programming through Partnerships was I

303
00:27:53.240 --> 00:27:57.679
thought a really cool area I had showed
that Partnerships um slide a while back

304
00:27:57.679 --> 00:28:00.840
where a lot of new and Innovative
Partnerships got built during the

305
00:28:00.840 --> 00:28:06.320
pandemic and several of you uh told us
that you had maintained some of those

306
00:28:06.320 --> 00:28:11.159
new Partnerships and that especially if
you didn't have any additional costs to

307
00:28:11.159 --> 00:28:15.279
um partner with those organizations you
could continue some of that

308
00:28:15.279 --> 00:28:19.279
programming and finally offerings for
individuals with disabilities and

309
00:28:19.279 --> 00:28:24.240
speakers of languages other than English
um we heard that some of these uh

310
00:28:24.240 --> 00:28:29.559
activities have continued um
specifically uh for for uh libraries

311
00:28:29.559 --> 00:28:34.519
ended up investing in things like
translated materials or audiobooks um

312
00:28:34.519 --> 00:28:39.279
and once you have those um resources you
can continue to use them so you see this

313
00:28:39.279 --> 00:28:43.720
expanding of um accessible

314
00:28:45.559 --> 00:28:52.240
resources I amoss was also very
interested in equity um the question of

315
00:28:52.240 --> 00:28:57.360
we have these huge um influxes of
funding and how do you get that funding

316
00:28:57.360 --> 00:29:03.080
out to the whole state in a way where
those who need it have

317
00:29:03.960 --> 00:29:08.760
it one way that states approached this
is to use formula funding approaches

318
00:29:08.760 --> 00:29:13.640
this was of course not the only way um
but one thing that some states did was

319
00:29:13.640 --> 00:29:17.640
um work out a formula mathematical
formula where they could figure out how

320
00:29:17.640 --> 00:29:22.440
much uh funding would go to each Library
um and they Incorporated soci economic

321
00:29:22.440 --> 00:29:26.760
variables like unemployment rates
poverty rates and Broadband

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00:29:26.760 --> 00:29:32.480
access we also learned a lot from our
program officer interviews and slaa um

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00:29:32.480 --> 00:29:37.000
interviews from program officers we
heard that projects really did um ended

324
00:29:37.000 --> 00:29:41.399
up serving historically less well served
communities which is great to hear um we

325
00:29:41.399 --> 00:29:45.919
did also hear that there um were some
tricky areas um some sort of challenges

326
00:29:45.919 --> 00:29:50.279
in terms of equ equitable distribution
of funding for example um there were

327
00:29:50.279 --> 00:29:54.440
differences between states that affected
distribution like the state size the

328
00:29:54.440 --> 00:29:59.080
State political climate and libraries
earlier experience applying for Grants

329
00:29:59.080 --> 00:30:02.880
and so that last one came sort of from
competitive funding where if if you were

330
00:30:02.880 --> 00:30:07.399
a library where you could already um
apply for a Federal grant you were in a

331
00:30:07.399 --> 00:30:10.279
much better place to apply for these
funds than a library that had never done

332
00:30:10.279 --> 00:30:15.240
that
before on the SLA a side um this was

333
00:30:15.240 --> 00:30:20.600
interesting um I think the the question
was an important one and um because of

334
00:30:20.600 --> 00:30:25.679
ongoing diversity Equity accessibility
and inclusion debates in many states um

335
00:30:25.679 --> 00:30:30.080
not all SLA representatives were able to
our questions but we did hear from a lot

336
00:30:30.080 --> 00:30:34.919
and um some of the things that States
considered um when Distributing funds

337
00:30:34.919 --> 00:30:39.200
included Community needs library and
programmatic needs uh geographic

338
00:30:39.200 --> 00:30:42.399
distribution of the funds making sure
that the funding reached their whole

339
00:30:42.399 --> 00:30:47.279
state um and other local and Regional
demographic statistics like the ones

340
00:30:47.279 --> 00:30:50.279
I've
mentioned and another thing that we

341
00:30:50.279 --> 00:30:56.240
heard from slas was that um one big
challenge was in states where there were

342
00:30:56.240 --> 00:31:01.120
several um Urban Metropolitan and
regions surrounded by um suburbs and

343
00:31:01.120 --> 00:31:06.960
then rural areas one really tricky thing
was meeting the needs of those different

344
00:31:06.960 --> 00:31:11.200
and diverse communities and so that was
a thing that states were grappling with

345
00:31:11.200 --> 00:31:14.760
and so I think um what you can take from
this slide is that there were different

346
00:31:14.760 --> 00:31:20.320
approaches to um to consider how to
distribute funding um but that

347
00:31:20.320 --> 00:31:24.840
definitely varied on state context as
much does

348
00:31:25.440 --> 00:31:31.080
so the last topic uh wanted wanted to
address was Lessons Learned From the uh

349
00:31:31.080 --> 00:31:35.559
pandemic what did we learn from these uh
funding

350
00:31:36.279 --> 00:31:43.120
efforts one of our research questions
was about using the existing granting

351
00:31:43.120 --> 00:31:47.799
structure that imls has this gr States
program and distributing money in the

352
00:31:47.799 --> 00:31:53.519
same way um one of the nice things about
nice things about the pandemic the

353
00:31:53.519 --> 00:31:58.120
pandemic is not nice um but I think one
of the fortunate things is having this

354
00:31:58.120 --> 00:32:01.720
Grand to States program set up so that
imls has a way to distribute funding to

355
00:32:01.720 --> 00:32:05.679
States and states are set up to
distribute funding around their states

356
00:32:05.679 --> 00:32:10.399
um but we wanted to know about how well
that worked in this pandemic

357
00:32:10.399 --> 00:32:13.720
context we talked to program officers
and they mentioned a number of

358
00:32:13.720 --> 00:32:19.440
challenges including timing and so I
know a lot of States um confirmed that

359
00:32:19.440 --> 00:32:23.600
um ARA was a huge influx of money and it
was very hard to expend all the funds

360
00:32:23.600 --> 00:32:27.480
within the arbit timeline so that was
one timing challenge supply chain issues

361
00:32:27.480 --> 00:32:30.960
came up and so it was um you know
projects could get delayed because of

362
00:32:30.960 --> 00:32:36.799
supply chain issues um bureaucratic
challenges came up both um mentioned by

363
00:32:36.799 --> 00:32:42.120
program officers and
slas um turnover and staff was another

364
00:32:42.120 --> 00:32:49.000
issue and um I think uh legislator
scrutiny came up as another interesting

365
00:32:49.000 --> 00:32:52.120
uh topic that was sort of
government-wide that of course um

366
00:32:52.120 --> 00:32:56.399
responsible spending is important um and
so legislators are concerned about where

367
00:32:56.399 --> 00:33:00.120
spending is going but of course of
course that means that um sometimes

368
00:33:00.120 --> 00:33:05.159
processes can be slowed down um in order
to make sure that we're um we're

369
00:33:05.159 --> 00:33:09.120
transparent and then U finally Grant
allowances came up sometimes and I think

370
00:33:09.120 --> 00:33:11.639
this foreshadows some of the stuff that
Emily will talk about with

371
00:33:11.639 --> 00:33:16.480
infrastructure that some people wanted
to um would have liked to use the funds

372
00:33:16.480 --> 00:33:19.639
for construction but obviously that's
not an allowable cost but could have

373
00:33:19.639 --> 00:33:22.880
been helpful in the times of Co like if
you wanted to tear down a wall and build

374
00:33:22.880 --> 00:33:28.039
a window or something like that can't do
that but um some states mentioned that

375
00:33:28.039 --> 00:33:31.559
the allowable costs were a

376
00:33:32.679 --> 00:33:38.440
challenge there were of course benefits
to the funding structure and um that

377
00:33:38.440 --> 00:33:43.360
came what came up most in the interviews
was that having this flexibility was one

378
00:33:43.360 --> 00:33:49.279
of the best things about um how these
funds came to you all um needs changed a

379
00:33:49.279 --> 00:33:56.159
lot during the pandemic and um the
flexibility of funding meant that uh

380
00:33:56.159 --> 00:34:00.679
States could pivot um um the volume of
funding was also quite important because

381
00:34:00.679 --> 00:34:05.240
there was just this unprecedented level
of need and then other grantees

382
00:34:05.240 --> 00:34:09.800
mentioned uh that the flexibility of
funding aligned very well with digital

383
00:34:09.800 --> 00:34:12.320
inclusion

384
00:34:15.040 --> 00:34:19.200
needs we wanted to hear about the SLA
experience and I know this has been an

385
00:34:19.200 --> 00:34:23.560
ongoing conversation but we thought this
was important just to reiterate um you

386
00:34:23.560 --> 00:34:27.119
know slas really did feel the weight of
supporting their communities and

387
00:34:27.119 --> 00:34:32.079
libraries um some slas reported feeling
as if they were sort of vehicles for

388
00:34:32.079 --> 00:34:37.240
providing funds to libraries um and we
had to recognize that when um funding

389
00:34:37.240 --> 00:34:41.879
doubled or quadrupled that also meant
double or quadruple workload um and so

390
00:34:41.879 --> 00:34:45.639
that was very
challenging um and then um staff also

391
00:34:45.639 --> 00:34:49.639
mentioned that they were dealing with
personal pandemic related issues while

392
00:34:49.639 --> 00:34:54.960
simultaneously ma managing these
doubling and quadrupling of work and so

393
00:34:54.960 --> 00:34:58.960
um that was an incredibly difficult
situation

394
00:34:58.960 --> 00:35:03.440
and all that being true I do want to say
kudos to you all because somehow you got

395
00:35:03.440 --> 00:35:09.079
through it um and and made a really huge
impact and so I think I mentioned the

396
00:35:09.079 --> 00:35:13.920
stats before that you reached over
40,000 libraries over 350 museums and

397
00:35:13.920 --> 00:35:20.079
over 80 tribal institutions so um it
speaks to all of your hard dedicated

398
00:35:20.079 --> 00:35:25.960
work that um you are able to effectively
and efficiently um distribute this

399
00:35:25.960 --> 00:35:34.240
funding slaa also noted that there were
some issues um with our with um that

400
00:35:34.240 --> 00:35:40.079
that made it more challenging for them
such as strict uh spending timelines and

401
00:35:40.079 --> 00:35:45.119
also um reporting requirements that was
a challenge but they also said something

402
00:35:45.119 --> 00:35:49.720
that mitigated that challenge was that
IMS um really professionally managed

403
00:35:49.720 --> 00:35:53.960
their grants um and that they put a lot
of thoughtfulness and structure into

404
00:35:53.960 --> 00:35:57.640
their programs which make them an asset
to SL laas and the Library community and

405
00:35:57.640 --> 00:36:02.319
and I'm not in the grand States program
so I just want to say they're awesome um

406
00:36:02.319 --> 00:36:06.000
and we heard it from you and you're

407
00:36:07.079 --> 00:36:11.160
awesome in terms of overcoming
challenges how did you all do this um we

408
00:36:11.160 --> 00:36:14.440
asked a lot about that and we heard that
there were several strategies to

409
00:36:14.440 --> 00:36:19.280
distribute funds quickly that included
using formula based approaches um not

410
00:36:19.280 --> 00:36:23.920
everyone did that but that was one way
um both procurement Solutions were

411
00:36:23.920 --> 00:36:29.000
common in order uh to make it so that
libraries don't have to procure say mass

412
00:36:29.000 --> 00:36:33.720
or PPE um one by one uh States could do
it at the state

413
00:36:33.720 --> 00:36:40.319
level a lot of um or I should say some
states um did not have an electronic

414
00:36:40.319 --> 00:36:45.000
grants management system at the start of
all this but were able to set one up um

415
00:36:45.000 --> 00:36:49.200
during the pandemic um that made it
challenging of of course at first but

416
00:36:49.200 --> 00:36:54.400
made it more possible to deal with the
arpa influx of funding um

417
00:36:54.400 --> 00:36:58.800
after SLA a mentioned restructuring
staff responsibilities to handle their

418
00:36:58.800 --> 00:37:02.960
work increases and they also some
mentioned allocating administrative and

419
00:37:02.960 --> 00:37:07.599
purchasing responsibilities to Regional
Library

420
00:37:08.160 --> 00:37:12.680
cooperatives this actually brings me to
the conclusion um I may have skipped

421
00:37:12.680 --> 00:37:16.640
some slides so asked questions because
there there's there's some content in in

422
00:37:16.640 --> 00:37:22.760
The Ether um but um the the four
conclusions that our contractor came to

423
00:37:22.760 --> 00:37:27.520
that we really wanted to just sort of
leave you with are um slas use different

424
00:37:27.520 --> 00:37:30.720
different methods to distribute funds
but worked to achieve efficient and

425
00:37:30.720 --> 00:37:35.760
equitable distribution of funding slaa
took advantage of the transition to

426
00:37:35.760 --> 00:37:40.240
Virtual environments to expand Library
access to SLA meetings through digital

427
00:37:40.240 --> 00:37:44.319
teleconferencing platforms and virtual
professional development

428
00:37:44.319 --> 00:37:49.079
opportunities on the library side uh
libraries modified existing programming

429
00:37:49.079 --> 00:37:53.960
and created new programming to meet the
needs um of their communities um and

430
00:37:53.960 --> 00:37:58.839
libraries especially work to bridge the
digital divide exacerbated by the p pmic

431
00:37:58.839 --> 00:38:02.640
and finally although many libraries
initially viewed new programming as a

432
00:38:02.640 --> 00:38:07.160
temporary response to the covid-19
pandemic um many continue to offer the

433
00:38:07.160 --> 00:38:12.880
programs and services created during the
pandemic and so um the last thing I'd

434
00:38:12.880 --> 00:38:15.640
like to do is just acknowledge all the
hard work of everybody in this room I

435
00:38:15.640 --> 00:38:19.640
was not here but I was so impressed when
I saw this data so I'm just to

436
00:38:19.640 --> 00:38:23.960
congratulations to you all for braving a
hard time and and serving everyone that

437
00:38:23.960 --> 00:38:28.880
you did um and I also want to thank you
all because um you all provided the data

438
00:38:28.880 --> 00:38:32.119
um that is coming here and I know some
of this is a repeat of what you told us

439
00:38:32.119 --> 00:38:37.720
but it'll also help um the government
and other communities learn about um how

440
00:38:37.720 --> 00:38:43.160
imls successfully um responded and I'm
going to bring uh the wonderful Emily up

441
00:38:43.160 --> 00:38:47.880
uh to field some questions if we we have
a few minutes for

442
00:38:48.210 --> 00:38:58.480
[Applause]
questions hi sorry so um the slide where

443
00:38:58.480 --> 00:39:06.520
you give the numbers of libraries tribal
units and something else that got Awards

444
00:39:06.520 --> 00:39:12.680
yep that was with cares and arpa
together yes and are those unique

445
00:39:12.680 --> 00:39:17.560
um yeah I believe that um uh so I we did
have our contractor perform the data

446
00:39:17.560 --> 00:39:20.520
analyses but I believe they do
duplicated I'm looking yeah Terry says

447
00:39:20.520 --> 00:39:25.520
yes they do duplicated unique
institutions thanks s so each so 40,000

448
00:39:25.520 --> 00:39:29.880
different libraries yes okay and how
does that compare to your benchmark year

449
00:39:29.880 --> 00:39:35.760
of 2019 that's a great question um I so
I think our contractor had noted that it

450
00:39:35.760 --> 00:39:42.720
might be slightly less than a benchmark
here um I don't know exactly why that is

451
00:39:42.720 --> 00:39:48.599
because obviously was a lot of funding
um I'm I I don't have a great answer for

452
00:39:48.599 --> 00:39:54.200
that but we could dig a little more it's
a really good question

453
00:40:00.090 --> 00:40:03.260
[Music]

454
00:40:12.760 --> 00:40:19.960
um we could potentially some
results bear with me for those of you

455
00:40:19.960 --> 00:40:28.440
who were on this side of morning you
have come into your state liar post pic

456
00:40:51.640 --> 00:40:59.240
people for the people who were coming on
right in the middle of it what is

457
00:41:13.400 --> 00:41:15.880
especially

458
00:41:16.960 --> 00:41:22.760
people what's your take from

459
00:41:27.640 --> 00:41:30.640
and

460
00:41:57.960 --> 00:42:00.680
Fant

461
00:42:08.560 --> 00:42:12.760
J thank you

462
00:42:54.040 --> 00:42:57.040
app

463
00:43:05.480 --> 00:43:10.319
thank you thanks for the example that's
like I love The Illuminating insights

464
00:43:10.319 --> 00:43:13.319
thank you

465
00:43:26.119 --> 00:43:30.440
awesome so when I I think about

466
00:43:50.839 --> 00:43:59.040
that I think the were put in place right
but as we look at fure

467
00:44:16.880 --> 00:44:20.359
yeah and I don't know the answer but
Clifton's showing data and I'm really

468
00:44:20.359 --> 00:44:24.839
curious now too so thank
you sorry to set you up if I don't know

469
00:44:24.839 --> 00:44:28.559
if that's in yours but

470
00:44:28.599 --> 00:44:33.800
pulling from The Well of knowledge um I
just wanted to reiterate the the midlife

471
00:44:33.800 --> 00:44:37.680
crisis thing did
really um I was working with the State

472
00:44:37.680 --> 00:44:41.079
Library agency but I didn't become the
LCA coordinator till the middle of the

473
00:44:41.079 --> 00:44:45.319
pandemic so I sort of saw what my
predecessor uh was doing so it really

474
00:44:45.319 --> 00:44:52.240
did resonate that we did so much work in
such a short amount of time um but I

475
00:44:52.240 --> 00:44:55.599
also just wanted to say I was very
skeptical at the beginning I think it

476
00:44:55.599 --> 00:44:59.839
was in Baltimore when when Crosby keer
was talking about why we had to spend

477
00:44:59.839 --> 00:45:05.599
the money so fast um I feel like I
probably rolled my eyes uh quite a bit

478
00:45:05.599 --> 00:45:10.559
and was like that's uh ridiculous but
seeing how you know some of the other

479
00:45:10.559 --> 00:45:13.720
political entities that received funding
and I think you mentioned this right

480
00:45:13.720 --> 00:45:18.880
imls handled this so well and it was so
professionally done and libraries Rose

481
00:45:18.880 --> 00:45:22.400
the occasion so well um and my
colleagues right and I think our State

482
00:45:22.400 --> 00:45:27.280
Library agencies did as well that um I
feel really proud to have spent this

483
00:45:27.280 --> 00:45:32.240
money and done these projects in the way
that we did even though it was sort

484
00:45:32.240 --> 00:45:37.760
of Soul crushing is a strong phrase but
it was it was very challenging in the

485
00:45:37.760 --> 00:45:43.760
moment but in retrospect I do think it
provides a very strong argument going

486
00:45:43.760 --> 00:45:51.800
forward for why libraries are a smart
investment uh for federal and state

487
00:45:53.760 --> 00:46:02.040
dollars thank you we will take with
us jennif

488
00:46:02.040 --> 00:46:06.599
last yeah sorry this is I know it's a
little uh extra than above what you

489
00:46:06.599 --> 00:46:11.960
asked for but I just wanted to say that
even as it was kind of Soul crushing and

490
00:46:11.960 --> 00:46:17.880
there was so much work I mean I I felt
so um I I just felt really honored to be

491
00:46:17.880 --> 00:46:22.839
able to have something I could do that
would actually be helpful that I think

492
00:46:22.839 --> 00:46:28.040
the for us the psychological benefits
actually outweighed you know the soul

493
00:46:28.040 --> 00:46:33.079
crushing work which was Soul crushing
but um in you know in the end I mean I

494
00:46:33.079 --> 00:46:37.920
think we came out feeling a whole lot
better than we would have

495
00:46:37.920 --> 00:46:40.920
otherwise

496
00:46:51.079 --> 00:46:57.960
em access to information acoss State a
EMP

497
00:46:57.960 --> 00:47:00.079
it

498
00:47:01.559 --> 00:47:05.559
seems the

499
00:47:55.319 --> 00:47:58.319
you're

500
00:48:09.880 --> 00:48:16.530
[Applause]

501
00:48:17.640 --> 00:48:22.480
thank you all right I am feeling
inspired despite how many times the word

502
00:48:22.480 --> 00:48:28.720
Soul crushing was tossed out there I am
reminded like viscerally there in the

503
00:48:28.720 --> 00:48:33.800
time that you all were just being Heroes
so thank you again it was really great

504
00:48:33.800 --> 00:48:39.319
to see this incapsulated Lisa you did a
fabulous job sorry about the slides um

505
00:48:39.319 --> 00:48:45.760
we we appreciate you so much um now
we're going to see the flip side of the

506
00:48:45.760 --> 00:48:50.319
data which is what was going on with the
allotment grants in the meantime and

507
00:48:50.319 --> 00:48:55.559
what is the longitudinal look at what
our allotment grants have been doing we

508
00:48:55.559 --> 00:49:00.240
haven't actually done
this flavor of presentation for a number

509
00:49:00.240 --> 00:49:05.200
of years we kind of parked it all on
hold because the pandemic was going on

510
00:49:05.200 --> 00:49:10.240
there were other priorities happening
but this year early in our planning we

511
00:49:10.240 --> 00:49:14.200
said this is what we want to do this
again it's really important the states

512
00:49:14.200 --> 00:49:19.599
give us all this data through the spr we
don't want it to go into a black box we

513
00:49:19.599 --> 00:49:25.400
want to tell the national story and to
do right by you as stewards of this data

514
00:49:25.400 --> 00:49:29.520
and can we please have that kind of
presentation again we know that the

515
00:49:29.520 --> 00:49:33.440
person that gave that presentation
doesn't work and I am a less anymore but

516
00:49:33.440 --> 00:49:39.160
you work magic Matt bur Bal so make it
happen for us and he did and let me just

517
00:49:39.160 --> 00:49:43.799
say that um Clifton has only been
working with this data for a few short

518
00:49:43.799 --> 00:49:49.359
months and also comes from outside of
libraries and so this is an actual

519
00:49:49.359 --> 00:49:53.960
Miracle what you're about to see is that
he synthesized all of it and put it

520
00:49:53.960 --> 00:49:57.680
together in a way that I think will
spark conversation

521
00:49:57.680 --> 00:50:02.200
um you know Clifton is a past educator
he brings a lot of good curiosity to

522
00:50:02.200 --> 00:50:08.079
this work he's also very funny and very
kind and I'm so pleased that you get to

523
00:50:08.079 --> 00:50:16.350
hear from him today and see some of your
data in action so please help me welcome

524
00:50:16.350 --> 00:50:25.640
[Applause]
Clifton hello um I was hired for height

525
00:50:25.640 --> 00:50:31.760
so I'm not going to adjust my
microphone so it it sounds like um I'm

526
00:50:31.760 --> 00:50:38.359
being projecting pretty well um hello my
name is uh Clifton MC reyolds and um I'm

527
00:50:38.359 --> 00:50:43.480
going to introduce myself I grew up in
extreme Southern

528
00:50:43.480 --> 00:50:48.440
Illinois um I was not allowed in the
early 80s to go to a library because

529
00:50:48.440 --> 00:50:52.240
where we lived was no we were not
Incorporated anywhere so I was not able

530
00:50:52.240 --> 00:50:57.520
to I I was allowed to go to the library
once or twice before school and wasn't

531
00:50:57.520 --> 00:51:01.720
allowed to check anything out um but uh
now it's interesting how it's a full

532
00:51:01.720 --> 00:51:07.240
circle I've been able to visit archives
um several countries and um just really

533
00:51:07.240 --> 00:51:14.520
en enjoy the resource in libraries and
museums and all other kind of fun things

534
00:51:14.520 --> 00:51:21.040
um I have a background in education um
my PhD is in research methodology and

535
00:51:21.040 --> 00:51:28.480
evaluation um I taught high school music
and

536
00:51:28.480 --> 00:51:36.960
math so now you'll understand why I'm so
weird um I I I was told originally that

537
00:51:36.960 --> 00:51:43.640
you came to this conference just for
graphs and charts is that that is oh

538
00:51:43.640 --> 00:51:49.000
that might be correct or incorrect but I
have some charts um for you um I was

539
00:51:49.000 --> 00:51:53.920
reminded that there are some principles
to kind of go forth um between the

540
00:51:53.920 --> 00:51:59.960
communication between um the branch and
the states and it's the couple

541
00:51:59.960 --> 00:52:06.839
principles we wanted to remind you of
was that it this whole spr is a

542
00:52:06.839 --> 00:52:10.920
partnership program it's we're not going
to be able to do anything with the data

543
00:52:10.920 --> 00:52:14.680
unless you do something with the data
and give it to us so it's very much hand

544
00:52:14.680 --> 00:52:19.960
inand
a frolicking through a field of flowers

545
00:52:19.960 --> 00:52:25.720
of data it's wonderful um so it's it's
it's great we can't do this without your

546
00:52:25.720 --> 00:52:32.000
help um we and your participation and
your input so it's very important we

547
00:52:32.000 --> 00:52:37.160
really appreciate it uh I I am the kind
of person that enjoys digging deep into

548
00:52:37.160 --> 00:52:42.960
data and it was wonderful I I really
liked looking at the tables um and so

549
00:52:42.960 --> 00:52:46.640
one of the first things we did is we
knew that we were going to exclude the

550
00:52:46.640 --> 00:52:50.480
car's arpa data so what you're about to
see is just some analysis some Trend

551
00:52:50.480 --> 00:52:55.760
analysis some charts and stuff that
exclude what um what Lisa was just

552
00:52:55.760 --> 00:53:02.000
talking about so
um now over the next 45 minutes um I

553
00:53:02.000 --> 00:53:05.000
understand like I said I was a former
teacher if you need to stand up that's

554
00:53:05.000 --> 00:53:08.359
no problem to me if you need to stretch
your legs it's not going to it's not

555
00:53:08.359 --> 00:53:12.839
going to bother me or distract me um but
you will be held accountable for the the

556
00:53:12.839 --> 00:53:19.440
pop quiz at the end of it so make sure
you're ready for that so um like Lisa

557
00:53:19.440 --> 00:53:24.599
had mentioned there are um six focal
areas with various intents that are

558
00:53:24.599 --> 00:53:31.680
mapped directly to them um this analysis
what we did today didn't go into um

559
00:53:31.680 --> 00:53:36.359
specific intents although we did look at
other kind of ways to slice and dice the

560
00:53:36.359 --> 00:53:41.839
data so um hopefully you'll find that um
interesting um but again you know this

561
00:53:41.839 --> 00:53:45.280
is just a
reminder um

562
00:53:45.280 --> 00:53:49.160
so luckily when I first looked at the
data one of the things I wanted to do is

563
00:53:49.160 --> 00:53:55.240
summarize and High Point some highlights
so uh these are some of the things that

564
00:53:55.240 --> 00:54:01.720
from the year fiscal year 2015 through
2022 again excluding the um the Caris

565
00:54:01.720 --> 00:54:04.920
and arpa these are some of the things
that just kind of like stood out to me

566
00:54:04.920 --> 00:54:13.079
so um over 10,000 projects U 465,000
presentations and performances two

567
00:54:13.079 --> 00:54:17.720
billion 2.4 billion items circulated I
think that's kind of awesome thank you

568
00:54:17.720 --> 00:54:23.960
Carl Sean for allowing me to say billion
over and over again um and just just

569
00:54:23.960 --> 00:54:27.040
some really positive things to kind of
know

570
00:54:27.040 --> 00:54:33.520
where the your efforts are going um so
and plus I got to use some really cool

571
00:54:33.520 --> 00:54:39.079
sides and
colors now the analysis that that I

572
00:54:39.079 --> 00:54:44.720
did when I started my well backtrack
just a little bit when I started my u

573
00:54:44.720 --> 00:54:48.280
career in evaluation one of the things
that always stuck out to me was the

574
00:54:48.280 --> 00:54:52.640
utilization aspect of evaluation I don't
like just throwing out information

575
00:54:52.640 --> 00:54:59.559
that's just there so I wanted to really
focus on what you could use um and if I

576
00:54:59.559 --> 00:55:03.200
threw if I if I did some analysis that
you didn't like or you didn't want to

577
00:55:03.200 --> 00:55:07.599
lose guess what we're going to have some
time at the end um there should be um a

578
00:55:07.599 --> 00:55:10.640
couple of note cards and pens on your
tables and that's how we're going to

579
00:55:10.640 --> 00:55:14.280
collect some data um and small activity
at the

580
00:55:14.280 --> 00:55:20.400
end um so I did a longitudinal analysis
so it's a lot of line graphs um

581
00:55:20.400 --> 00:55:26.039
forecasting um I use a 95% confidence
interval um so you'll see the middle

582
00:55:26.039 --> 00:55:30.000
line is like kind of generally where
it's at in the 95% and then you'll see

583
00:55:30.000 --> 00:55:35.599
some um lower and upper bounds so it's
not really extreme um but it'll kind of

584
00:55:35.599 --> 00:55:41.079
give you an idea um and so like I said
we talked about focal areas and intense

585
00:55:41.079 --> 00:55:46.599
um some activities drilling down from
programs to activities and the types of

586
00:55:46.599 --> 00:55:54.000
activities um and just for a reminder um
whenever I have some timelines um I

587
00:55:54.000 --> 00:55:59.119
always put like just a CO link so you'll
know that this is where Co happened

588
00:55:59.119 --> 00:56:02.599
because we have all forgotten we didn't
know there was a

589
00:56:02.599 --> 00:56:08.960
pandemic so this is an example um so
this is a number of projects um from

590
00:56:08.960 --> 00:56:12.839
2015 through
2022 um as you can see there was a

591
00:56:12.839 --> 00:56:19.000
general decline um up until about 2019
and then you can kind of see where the

592
00:56:19.000 --> 00:56:24.240
pandemic altered a few things in as far
as the number of projects but using some

593
00:56:24.240 --> 00:56:30.559
analysis um and some input from the the
grants EST States it's reflecting

594
00:56:30.559 --> 00:56:35.799
efficiency more than is anything that
the reporting into the spr is is more

595
00:56:35.799 --> 00:56:40.839
like condensing things condensing the
projects and and representing um the

596
00:56:40.839 --> 00:56:44.720
data a lot more efficiently so this is
not a negative uh thing it's not like

597
00:56:44.720 --> 00:56:51.200
we're you know restricting the number of
projects but given that um again looking

598
00:56:51.200 --> 00:56:55.720
at the the forecast with the 95%
confidence interval um you can kind of

599
00:56:55.720 --> 00:56:59.000
see
looking at some uh the software that we

600
00:56:59.000 --> 00:57:03.440
used use some Trend analysis and
seasonality as well so you can kind of

601
00:57:03.440 --> 00:57:07.680
see where it could go in um 23 and 24
which we'll get that data soon so we'll

602
00:57:07.680 --> 00:57:13.240
see how wrong or right that forecasting
is and just to kind of drill down a

603
00:57:13.240 --> 00:57:16.200
little bit more I looked at the number
of

604
00:57:16.200 --> 00:57:20.280
activities and again General decrease
usually because of the efficiency of the

605
00:57:20.280 --> 00:57:25.839
reporting into the into the
software okay um and again you can kind

606
00:57:25.839 --> 00:57:31.599
of see like you know the number of
activities um kind of went up in 2019

607
00:57:31.599 --> 00:57:37.559
but again because of the the the
pandemic and so on so forth um went up

608
00:57:37.559 --> 00:57:43.000
in 2021 and further down um but again
fluctuations in the efficiency of the

609
00:57:43.000 --> 00:57:47.039
reporting I think is the best uh the
best explanation for

610
00:57:47.039 --> 00:57:54.240
that
um now for this um for the budget slide

611
00:57:54.240 --> 00:57:58.839
I have do I have two slides that
represent the same thing um so in the

612
00:57:58.839 --> 00:58:04.559
green you'll see the median budget for
the lsta funds and then the blue is the

613
00:58:04.559 --> 00:58:09.920
overall funds um I'm not going to insult
your intelligence but I will still

614
00:58:09.920 --> 00:58:16.799
remind what median means it's the one
that's in this very middle of how 50% of

615
00:58:16.799 --> 00:58:21.480
the budgets were above and 50% of the
budgets were below the number that's

616
00:58:21.480 --> 00:58:30.319
represented um so you can kind of see
the the number in the greens the plural

617
00:58:30.319 --> 00:58:36.839
numbers in the green that's the words I
was looking for um going uh steadily up

618
00:58:36.839 --> 00:58:42.000
to 2018 down a little bit in 2019 and
you can kind of see it kind of starting

619
00:58:42.000 --> 00:58:46.760
to recover again this is without the
cares and Arbor funding so there's still

620
00:58:46.760 --> 00:58:53.359
um median um kind of increased for
that and then just to kind of look at

621
00:58:53.359 --> 00:58:58.319
those the the lsta on a timeline just
same numbers just in a different uh

622
00:58:58.319 --> 00:59:04.480
graph format um you can kind of see the
projection um would be continuing to

623
00:59:04.480 --> 00:59:08.680
increase for the most part um especially
through

624
00:59:08.680 --> 00:59:15.720
2024 um and then you know the extreme
95% out of bounds would have it increase

625
00:59:15.720 --> 00:59:22.000
faster but even the the lower increase
in 2024 would be relatively what it is

626
00:59:22.000 --> 00:59:26.960
in
2022 so

627
00:59:27.680 --> 00:59:33.520
now um as Lisa had mentioned in in her
presentation here are some uh

628
00:59:33.520 --> 00:59:40.640
distributions of activities by focal
area type or focal area and by type oh

629
00:59:40.640 --> 00:59:44.640
and this one okay I was going to say the
the last time I viewed the slides they

630
00:59:44.640 --> 00:59:49.160
had taken out the even number of years
but they're back in now that's fine and

631
00:59:49.160 --> 00:59:54.359
just to point out that procurement U and
I believe even Lisa mentioned this that

632
00:59:54.359 --> 00:59:57.280
procurement is in institutional capacity
capity only so that's why it's not

633
00:59:57.280 --> 01:00:02.559
distributed to the others um so these
types you can kind of see the

634
01:00:02.559 --> 01:00:09.880
distribution um across uh lifelong
learning for example the the instruction

635
01:00:09.880 --> 01:00:14.799
uh taking up the most the majority and
the content and etc etc now one of the

636
01:00:14.799 --> 01:00:18.839
things that I noticed again not being
too familiar with imls but looking at

637
01:00:18.839 --> 01:00:22.640
this was like okay look we have three
large ones and three small ones so I

638
01:00:22.640 --> 01:00:26.559
just kind of wanted to do another set of
slides that just kind of looked at

639
01:00:26.559 --> 01:00:34.599
um apples and apples and oranges and
oranges so these are um the three larger

640
01:00:34.599 --> 01:00:40.319
uh focal areas um information access
institutional capacity and lifelong

641
01:00:40.319 --> 01:00:45.880
learning and you can kind of see how
they related to each other between um or

642
01:00:45.880 --> 01:00:53.920
from 20 2015 through
2022 um again in 2020 you can kind of

643
01:00:53.920 --> 01:00:59.520
see a large reduction in in the lifelong
learning because it kind of shifted I

644
01:00:59.520 --> 01:01:05.760
think um
fundings um as well as the information

645
01:01:08.400 --> 01:01:12.000
access i' like to give a little time not
not

646
01:01:12.000 --> 01:01:16.720
for being weird I just want to you
there's lots of information out there

647
01:01:16.720 --> 01:01:20.839
make you feel uncomfortable I did that
when I was teaching algebra but that was

648
01:01:20.839 --> 01:01:25.480
beside the
point and so here are the three smaller

649
01:01:25.480 --> 01:01:31.039
ones and and again you can kind of see
um the distribution compared to the the

650
01:01:31.039 --> 01:01:35.079
other two um throughout the

651
01:01:41.440 --> 01:01:49.079
years primarily Civic engagement remains
um if not the most um always a second

652
01:01:49.079 --> 01:01:54.960
but also in human services and economic
and and um employment developments was

653
01:01:54.960 --> 01:01:57.839
also

654
01:01:59.400 --> 01:02:05.119
and then this is the just percentage of
types U or percentage of activities by

655
01:02:05.119 --> 01:02:10.160
type um as you can see the planning
evaluation and procurement and this is

656
01:02:10.160 --> 01:02:16.039
all of them all of the projects together
so um just some kind of percentage

657
01:02:16.039 --> 01:02:22.279
distributions um instruction taking
about half most of the time um sometimes

658
01:02:22.279 --> 01:02:28.680
content being um representing a little
bit more especially in 2020 but again

659
01:02:28.680 --> 01:02:33.559
the kesara kind of redistributed and
shifted around

660
01:02:36.520 --> 01:02:42.520
thing and by format so this is
particularly the instruction

661
01:02:42.520 --> 01:02:48.559
activities and um just the number of
activities by uh format whether it be

662
01:02:48.559 --> 01:02:54.240
virtual or combined or in person um so
the in person is on the bottom and then

663
01:02:54.240 --> 01:02:59.480
the virtual is on top and this is just a
reflection of of what happens to a

664
01:02:59.480 --> 01:03:04.559
planet when they go through a pandemic
right it's just it's shifted to mostly

665
01:03:04.559 --> 01:03:10.640
in person and now it's about you know
evenly distributed and

666
01:03:10.640 --> 01:03:15.880
um and a blend a mix of combination in
person and virtual like we were doing

667
01:03:15.880 --> 01:03:19.880
today hello people in the Internet by
the

668
01:03:19.880 --> 01:03:26.920
way oh are they oh cool I'm glad to know
that that's

669
01:03:28.440 --> 01:03:34.680
and the last um informational slide um I
just wanted to show you was this is just

670
01:03:34.680 --> 01:03:39.279
my curiosity was I wanted to know how
the distribution of well I started with

671
01:03:39.279 --> 01:03:45.279
minutes but it's hard to comprehend tens
of thousands of minutes so I did um the

672
01:03:45.279 --> 01:03:51.000
number of session hours um by focal area
and I thought this was really

673
01:03:51.000 --> 01:03:58.119
interesting um that institutional
capacity was for 47 to 58% of the number

674
01:03:58.119 --> 01:04:01.520
of
sessions but

675
01:04:01.520 --> 01:04:07.559
81% to 96% of the hours distributed so
that's interesting and it just means

676
01:04:07.559 --> 01:04:13.039
that probably things are
longer longer sessions um instruction

677
01:04:13.039 --> 01:04:20.079
instructors like to talk a lot so I'm
trying not to do that um so um yeah

678
01:04:20.079 --> 01:04:24.680
Library operations and
infrastructure about half of the uh

679
01:04:24.680 --> 01:04:32.200
sessions but only like 4 to 20% of the
hours so um anyway this just an

680
01:04:32.200 --> 01:04:37.160
interesting um distribution of like of
how things were um and these are

681
01:04:37.160 --> 01:04:42.599
thousands of hours by the way
not no not just in number of hours but

682
01:04:42.599 --> 01:04:47.680
these are thousands of hours so um just
kind of

683
01:04:47.680 --> 01:04:54.520
that now I would like to do an
activity um just based off of what we

684
01:04:54.520 --> 01:04:58.319
just saw what you know about the spr spr
if you if you've gone to these uh

685
01:04:58.319 --> 01:05:05.160
conferences these meetings
before what are some things that um when

686
01:05:05.160 --> 01:05:10.680
you think of the spr what comes to mind
that sort of thing um there is somebody

687
01:05:10.680 --> 01:05:14.559
on um you're collecting the information
from the virtual

688
01:05:14.559 --> 01:05:20.400
people um
so if you wouldn't mind let's do the

689
01:05:20.400 --> 01:05:24.480
Green Card first so everybody should
have a green card and a pen a writing

690
01:05:24.480 --> 01:05:27.480
utensil

691
01:05:29.160 --> 01:05:37.839
and my algebra 2 class that had 28
football players in it please write

692
01:05:37.839 --> 01:05:43.039
legibly I should remind you that yes
that that was the most interesting um

693
01:05:43.039 --> 01:05:49.079
algebra class I had ever
taught 30 students 28 boys that were

694
01:05:49.079 --> 01:05:54.200
football
players okay that's why we're flexible

695
01:05:54.200 --> 01:05:59.520
sometimes but yeah it's very interesting
learning Dynamic let me tell you um so

696
01:05:59.520 --> 01:06:04.520
keep in mind these are confidential I do
not know your personal writing styles um

697
01:06:04.520 --> 01:06:10.760
so um uh don't feel like we're going to
call you out or anything this is just

698
01:06:10.760 --> 01:06:16.000
kind of like an internal evaluation
where are we going forward with the spr

699
01:06:16.000 --> 01:06:18.880
what do you want to see that kind of
thing so

700
01:06:18.880 --> 01:06:24.559
um your instructions and this is the
hard part don't write anything

701
01:06:24.559 --> 01:06:33.319
yet take a few moments and think about
only one or two

702
01:06:33.319 --> 01:06:39.440
words that come to mind when you want to
describe the spr reports or this

703
01:06:39.440 --> 01:06:44.279
presentation okay just one or two

704
01:06:45.880 --> 01:06:54.440
words just think about them for
now one or two and dear Librarians if

705
01:06:54.440 --> 01:07:00.640
you want to use hyphenated
or that's up to you but one or two

706
01:07:00.640 --> 01:07:08.480
words okay now write down those words on
one side of the green

707
01:07:10.920 --> 01:07:16.640
card and then on the back you're going
to tell me why you chose those one or

708
01:07:16.640 --> 01:07:22.079
two
words just use a couple of sentences and

709
01:07:22.079 --> 01:07:26.880
those sentences may not be the following
dissertation describes the what the

710
01:07:26.880 --> 01:07:31.559
choice I
made this is really

711
01:07:31.559 --> 01:07:34.880
in-depth data

712
01:07:34.960 --> 01:07:39.200
collection again the spr report or the
presentation what would you what do you

713
01:07:39.200 --> 01:07:43.839
think
about and why the sentences and if you

714
01:07:43.839 --> 01:07:47.680
and if you just write it on one side
that's okay and then the virtual

715
01:07:47.680 --> 01:07:52.319
people type in your words and then
hyphen your your sentences I guess

716
01:07:52.319 --> 01:07:57.480
you're not over there virtual people are
over here so just type in your your word

717
01:07:57.480 --> 01:08:02.000
and then a sentence or two describing
why you chose that

718
01:08:16.120 --> 01:08:21.880
word you thought I was kidding about the
prop quiz didn't you

719
01:08:30.839 --> 01:08:38.239
okay and um when you are finished
um I'll collect them later um just make

720
01:08:38.239 --> 01:08:41.480
sure they're in the pile on the table
that I'll be able to see and I'll

721
01:08:41.480 --> 01:08:47.560
collect them um or or we can if you want
to do that now you

722
01:08:50.839 --> 01:08:56.880
can and then an optional thing if you
want to use the the pink card to just

723
01:08:56.880 --> 01:09:01.520
kind of like any additional comments
like please don't wear a blue tie to

724
01:09:01.520 --> 01:09:06.880
this meeting ever again okay that's fine
again confidential but that's for other

725
01:09:06.880 --> 01:09:12.520
that's why we can keep the the pink and
the green cards separate um please don't

726
01:09:12.520 --> 01:09:18.159
use the same card again I've worked with
teenagers so I feel like I have to say

727
01:09:18.159 --> 01:09:24.000
things like that um and again virtual if
you have something additional just type

728
01:09:24.000 --> 01:09:27.359
use your word as an additional

729
01:09:27.440 --> 01:09:32.319
um so that's that so with that in mind
um as you're write finishing your

730
01:09:32.319 --> 01:09:40.520
comments and and things um are there any
questions um that you might have about

731
01:09:40.520 --> 01:09:45.600
the
spr something that wasn't represented or

732
01:09:45.600 --> 01:09:51.679
something that you have a question about
that that was

733
01:09:51.679 --> 01:09:56.320
um I will do my best to answer now and
I've only I've only had this data for

734
01:09:56.320 --> 01:10:00.880
seven weeks so I'll do my

735
01:10:00.960 --> 01:10:04.280
best any

736
01:10:08.600 --> 01:10:11.719
questions if there are any questions
I'll start making up questions and then

737
01:10:11.719 --> 01:10:17.040
answering them like can you sort them
descending alphabetically well yes I can

738
01:10:17.040 --> 01:10:25.440
yes lots of fun uh I would like to set
you up for a question okay um which is

739
01:10:25.440 --> 01:10:30.960
we now have data on Caris and arpa and
we have data on covid and then we have

740
01:10:30.960 --> 01:10:37.080
the wonderful State data that came out
of our slaa

741
01:10:37.080 --> 01:10:44.560
survey can you or anyone from the team
talk about how we collectively within o

742
01:10:44.560 --> 01:10:53.360
can start connecting the
data how

743
01:10:53.360 --> 01:10:59.400
um have we talked about it
oh yes I get your question now yes we

744
01:10:59.400 --> 01:11:03.920
have talked about it and and that's
absolutely one of the next um steps that

745
01:11:03.920 --> 01:11:09.360
Lisa um and I think are um we're going
to Endeavor is just kind of like what

746
01:11:09.360 --> 01:11:14.320
was the overall picture um so we've
presented to you two different pictures

747
01:11:14.320 --> 01:11:21.520
split apart and uh we're going to work
on some analysis um about kind of

748
01:11:21.520 --> 01:11:26.480
building on Mora's question a little bit
and some of what we saw in Lisa slides

749
01:11:26.480 --> 01:11:32.360
and I believe we have one from the
virtual people we have a oh great

750
01:11:32.360 --> 01:11:36.040
and because there's going to be a
transcript I'm not going to use Nam

751
01:11:36.040 --> 01:11:40.920
going to do that
um question is are there questions you

752
01:11:40.920 --> 01:11:45.239
want to answer not sure you exactly I'm
assuming it's

753
01:11:45.239 --> 01:11:52.679
youan the larger VI but the doesn't
provide the data for that's one

754
01:11:52.679 --> 01:11:58.360
question and
data heavy that's their word data and

755
01:11:58.360 --> 01:12:04.960
heavy is their work the has a lot of
information components Tak a lot of time

756
01:12:04.960 --> 01:12:10.520
to collect but it is so satisfying when
it comes together oh

757
01:12:10.520 --> 01:12:17.000
good yeah it it is very data heavy but
you kind of need that to answer all

758
01:12:17.000 --> 01:12:23.239
sorts of different kinds of questions so
I found that oddly exciting about the

759
01:12:23.239 --> 01:12:26.320
working with the data it's that yeah
this is going to be able to answer a lot

760
01:12:26.320 --> 01:12:30.520
of the questions so but

761
01:12:31.520 --> 01:12:34.520
yes

762
01:12:38.560 --> 01:12:44.840
yes at the Lis of these cards you know
who I am but you know

763
01:12:44.840 --> 01:12:50.920
that's um when when I when I watch this
was Sting this report like in my mind I

764
01:12:50.920 --> 01:12:56.960
was known to the way we administer
programs L on the

765
01:12:56.960 --> 01:13:01.880
right it's really illustrating to me the
changes that we made with having more

766
01:13:01.880 --> 01:13:06.440
money and you
know those things I I would find it

767
01:13:06.440 --> 01:13:10.400
interesting
question

768
01:13:10.400 --> 01:13:15.280
somay
um I'd be interested in see how other

769
01:13:15.280 --> 01:13:20.000
programs last like Federal programs if
they're seeing the same of like

770
01:13:20.000 --> 01:13:25.760
increasing project size or other things
like that that we can learn from

771
01:13:25.760 --> 01:13:29.560
of what we do for libraries because I
think there's there's sort of two minds

772
01:13:29.560 --> 01:13:33.880
that we have this one is being a grand
administrator and the other is Library

773
01:13:33.880 --> 01:13:39.159
stuff and like to me I'm really
interested as a library guy to know more

774
01:13:39.159 --> 01:13:43.239
about Grant Administration like learn
more about that

775
01:13:43.239 --> 01:13:47.400
process yeah well we're certainly
looking at other Grant um

776
01:13:47.400 --> 01:13:52.520
administrations as well um yeah you're
right it is you know uh my previous role

777
01:13:52.520 --> 01:13:58.040
was in um graduate medical education it
was is so interesting to see similar you

778
01:13:58.040 --> 01:14:01.280
know reflection of what you know
different programs and and activities

779
01:14:01.280 --> 01:14:05.960
and stuff
too we have additional comments question

780
01:14:05.960 --> 01:14:10.199
um
dense the spr report is very dense with

781
01:14:10.199 --> 01:14:16.719
information and data procurement the
increase in purchasing technology other

782
01:14:16.719 --> 01:14:23.800
items during Co was reinforced by this
presentation good that's a a statement

783
01:14:23.800 --> 01:14:28.159
more than a question but yeah
good all right

784
01:14:28.159 --> 01:14:32.800
awesome yeah it and like I said um
sometimes you need dense things right

785
01:14:32.800 --> 01:14:36.920
the the most beautiful W wood that sings
in musical instruments are the densest

786
01:14:36.920 --> 01:14:42.400
wood so right we want our data to
sing a very

787
01:14:42.400 --> 01:14:53.239
back data analysis of this reinforces
dense I also happy that no any

788
01:14:55.320 --> 01:15:01.280
vot so far yeah plenty of things no

789
01:15:01.679 --> 01:15:10.320
words we can't wa great great the
virtual folks are coming in h great

790
01:15:10.320 --> 01:15:16.679
Su I think the way the was developed
allows the information input to be Su

791
01:15:16.679 --> 01:15:21.880
not everyone is
for accountability it's a lot of work to

792
01:15:21.880 --> 01:15:27.600
compile but is important to do in order
our efforts especially in regard to our

793
01:15:27.600 --> 01:15:33.400
efficient use of
funds

794
01:15:34.400 --> 01:15:39.639
great this is Terry in the back of the
room I'm just reflecting on Ben's

795
01:15:39.639 --> 01:15:50.480
observation about money and library was
very Wonder we felt like we an answer in

796
01:15:50.480 --> 01:15:58.840
some of's data I feel like
large share of what we see invested in

797
01:15:58.840 --> 01:16:05.679
and especially that last graph with the
white middle I think that kind of sums

798
01:16:05.679 --> 01:16:11.920
up yes like there is a lot of Library
professional Workforce Development at

799
01:16:11.920 --> 01:16:19.440
least in hours that is happening through
these dollars so I found

800
01:16:20.920 --> 01:16:25.080
that and also as a reminder if you have
any any additional questions that we and

801
01:16:25.080 --> 01:16:29.960
get to or like to knows we that's what
we call them if the parking lot is

802
01:16:29.960 --> 01:16:34.560
completely open and um more than just if
you have something directed I guess to

803
01:16:34.560 --> 01:16:40.600
the O um or to me I guess personally but
um yeah just let us

804
01:16:40.600 --> 01:16:47.040
know this might be more a suggestion but
when I see the data on consultation ref

805
01:16:47.040 --> 01:16:53.159
and things like that I have the
suspicion that we're all we're alling a

806
01:16:53.159 --> 01:16:58.320
differ
and it would be really nice to

807
01:17:03.520 --> 01:17:11.920
have and also what
cons how many times consult sometimes

808
01:17:11.920 --> 01:17:16.280
it's a
quiery little B longer but sometimes it

809
01:17:16.280 --> 01:17:21.840
on for days and I I suspect that

810
01:17:32.679 --> 01:17:36.600
sure when they're I'm always

811
01:17:38.280 --> 01:17:42.960
ofing yeah so that would be yeah thank
you very

812
01:17:42.960 --> 01:17:51.760
much have another word us virtual
transparency plus the imls public portal

813
01:17:51.760 --> 01:17:56.560
for searching projects demonstrates

814
01:18:03.520 --> 01:18:09.239
I'm just going to chime in on comment
because just like those valuation

815
01:18:09.239 --> 01:18:15.719
guidelines went
through cycle I'm a little scared the

816
01:18:15.719 --> 01:18:19.320
deadlines coming up
in2 so

817
01:18:19.320 --> 01:18:24.920
all
documentation requirements dat

818
01:18:24.920 --> 01:18:32.239
all to go through the sh again and this
might be a good we get

819
01:18:33.000 --> 01:18:39.480
oured so no
promises our be looking deep at those

820
01:18:39.480 --> 01:18:41.600
and

821
01:18:45.400 --> 01:18:51.960
we I believe the next item on the agenda
is a break are we ready for

822
01:18:51.960 --> 01:18:56.960
that yes
you gently back from

823
01:18:56.960 --> 01:19:01.960
break hello welcome

824
01:19:02.040 --> 01:19:07.040
back we still have you here we didn't
scare you away with

825
01:19:07.040 --> 01:19:11.520
data thank you for
returning i

826
01:19:11.520 --> 01:19:16.960
c I'm really excited for this session
partly because these are some of my

827
01:19:16.960 --> 01:19:23.800
favorite people here um Emily plom and
Frank I have to say is like if I could

828
01:19:23.800 --> 01:19:29.920
personify or embody a Swiss army knife
like she would be it she can do

829
01:19:29.920 --> 01:19:35.840
everything um we are so abundantly lucky
to work with her and she can match us

830
01:19:35.840 --> 01:19:42.280
point for point on goofiness so she
keeps us laughing all the time we love

831
01:19:42.280 --> 01:19:48.480
it uh and Matt burn bom directs all
these folks he's been sort of the silent

832
01:19:48.480 --> 01:19:54.360
uh voice until now and you're going to
get to hear from him he is a partner in

833
01:19:54.360 --> 01:20:00.520
this conference always committing to it
appreciating you he actually predates me

834
01:20:00.520 --> 01:20:04.480
and the rest of the grant to States team
in terms of working with

835
01:20:04.480 --> 01:20:10.920
you um the sheer amount of work that he
brings to his team is

836
01:20:10.920 --> 01:20:15.159
astounding um he has put this office on
a course with

837
01:20:15.159 --> 01:20:20.600
Destiny and um and and he manages to
still be very collegial and

838
01:20:20.600 --> 01:20:25.760
collaborative in all of this work with
other offices but my favorite part about

839
01:20:25.760 --> 01:20:32.199
Matt is that we're sort of Partners in
doing occasional fun morale building

840
01:20:32.199 --> 01:20:38.719
activities at the agency and I think um
for both of them here all of us can

841
01:20:38.719 --> 01:20:43.840
reflect on how we are as leaders in our
work and that we don't have to choose

842
01:20:43.840 --> 01:20:49.719
between the fun and the compassion side
of life or the getting stuff done side

843
01:20:49.719 --> 01:20:55.480
of life these two make sure that we do
both so it is my great pleasure to have

844
01:20:55.480 --> 01:21:02.800
them tell you about this new thing at
imls called The Learning agenda Emily

845
01:21:02.800 --> 01:21:05.440
Matt take it

846
01:21:05.500 --> 01:21:10.680
[Applause]

847
01:21:10.760 --> 01:21:15.600
away Emily you can pull bring that up
and I'll bring it

848
01:21:15.600 --> 01:21:21.440
down um I think I'm decided like a new
career for myself whatever I've left in

849
01:21:21.440 --> 01:21:27.800
my career it's um Talent acquisition I
want want to thank Emily Clifton Lisa

850
01:21:27.800 --> 01:21:33.280
today uh they r a third of our team
another member of our team who is been

851
01:21:33.280 --> 01:21:37.280
here today just to be observing is
Marissa I think about half of you know

852
01:21:37.280 --> 01:21:42.400
her from the public library survey the
SLA survey and as we start moving into

853
01:21:42.400 --> 01:21:48.000
the future we're going to be more
systematically relying on her knowledge

854
01:21:48.000 --> 01:21:51.960
and try to tell a more comprehensive
story from all the data and evidence

855
01:21:51.960 --> 01:21:56.560
that we have together so while we're
here please don't hesitate to reach out

856
01:21:56.560 --> 01:22:02.800
to M or the other members of our
team the um I also want to start by

857
01:22:02.800 --> 01:22:08.679
again thanking Cindy who's our leader
and our inspiration um for this

858
01:22:08.679 --> 01:22:13.920
particular topic today about the
learning agenda um I'm going to turn it

859
01:22:13.920 --> 01:22:18.560
to Emily pretty soon and she's going to
Jazz you up but just to set a little bit

860
01:22:18.560 --> 01:22:25.040
of the context um is if you can go back
to that to

861
01:22:25.040 --> 01:22:30.159
2020
21 and um we're in the middle of

862
01:22:30.159 --> 01:22:36.800
covid the agency also as a member of the
federal government it is uh doing its

863
01:22:36.800 --> 01:22:43.040
required updates of its strategic
planning and I'm Les as it finished its

864
01:22:43.040 --> 01:22:48.880
strategic plan we had a conversation
about should we do a learning agenda and

865
01:22:48.880 --> 01:22:52.199
we'll talk about a learning agenda in a
second but the story I want to tell

866
01:22:52.199 --> 01:22:57.280
right now is we weren't required to do
it we were too small and it's not really

867
01:22:57.280 --> 01:23:05.560
essential something for the bigger
agencies and Cindy Crosby larer

868
01:23:05.560 --> 01:23:11.199
migz agreed yeah this makes business
this makes good business sense we don't

869
01:23:11.199 --> 01:23:16.639
need to be mandated to do it let's do it
because it makes it makes good sense

870
01:23:16.639 --> 01:23:21.320
it's good use for the taxpayers it's a
good way for us to be effective and

871
01:23:21.320 --> 01:23:29.840
meaningful so 22 we finished the Strate
iic plan and Emily Cindy Crosby Lara

872
01:23:29.840 --> 01:23:34.960
were meeting regularly in trying to
think about what this learning agenda

873
01:23:34.960 --> 01:23:40.840
would be and within it comes child
reading and it's going to be some of the

874
01:23:40.840 --> 01:23:47.040
infrastructure study I'm just trying to
set the context now so this learning

875
01:23:47.040 --> 01:23:52.840
agenda in real simple plain English not
that Federal goblook of a learning

876
01:23:52.840 --> 01:23:58.880
agenda what it really is is it's a
strategic multi-year plan for an agency

877
01:23:58.880 --> 01:24:04.239
to figure out what research and
evaluation should it do and it should do

878
01:24:04.239 --> 01:24:10.159
the research and evaluation is if we can
transform the data into evidence in a

879
01:24:10.159 --> 01:24:13.199
way that will make a meaningful
difference on

880
01:24:13.199 --> 01:24:20.000
decisions we start with a premise that
people have strong values that really

881
01:24:20.000 --> 01:24:26.360
help dictate complex decisions people
have their intuition people have a lot

882
01:24:26.360 --> 01:24:30.679
of historical knowledge and you have the
con the knowledge that comes from

883
01:24:30.679 --> 01:24:34.520
informal conversations these are all
really vital

884
01:24:34.520 --> 01:24:38.800
bases and when we start thinking about
research and evidence we're trying just

885
01:24:38.800 --> 01:24:44.560
to fill the Gap thinking about how this
other base of evidence from research and

886
01:24:44.560 --> 01:24:49.920
evaluation can supplement what you know
intuitively from your own history from

887
01:24:49.920 --> 01:24:53.600
your informal
conversations so we were having this

888
01:24:53.600 --> 01:24:58.480
conversation what would a learning
agenda look like in imls what are the

889
01:24:58.480 --> 01:25:02.679
types of questions what types of ways
could we go and collect the evidence how

890
01:25:02.679 --> 01:25:07.360
can we use it how can what would the
process look like for making sure there

891
01:25:07.360 --> 01:25:12.800
learning so we have this kind of this
abstract exercise where we go over all

892
01:25:12.800 --> 01:25:19.040
the various types of research and
evaluation we can do and we can do some

893
01:25:19.040 --> 01:25:25.719
tradeoffs in terms of how scientifically
credible these different methods are

894
01:25:25.719 --> 01:25:31.080
and we can also then think about well
they all take different amounts of time

895
01:25:31.080 --> 01:25:35.920
they all cost a lot of money and we
don't have the luxury of having that

896
01:25:35.920 --> 01:25:40.800
time of having that money so how do we
make a strategic decision and what's the

897
01:25:40.800 --> 01:25:45.080
best evidence that can help us make a
meaningful difference in having to make

898
01:25:45.080 --> 01:25:47.440
certain

899
01:25:47.639 --> 01:25:52.960
decisions okay so we're spending 2023 in
these conversations with star to

900
01:25:52.960 --> 01:25:56.880
shapit and we look we had just finished
the Strategic plan and we're trying to

901
01:25:56.880 --> 01:26:01.719
identify those parts of the Strategic
plan where we wanted to make some change

902
01:26:01.719 --> 01:26:06.000
but our
intuition our informal conversations our

903
01:26:06.000 --> 01:26:11.280
values weren't providing enough evidence
to know how to move forward so we're now

904
01:26:11.280 --> 01:26:15.440
starting to think about what would that
research might look like and most

905
01:26:15.440 --> 01:26:20.239
importantly as we start being future
oriented if we can get some insights

906
01:26:20.239 --> 01:26:25.560
into this research before we launch any
new Grant making is there some way we

907
01:26:25.560 --> 01:26:30.360
might be able to structure those Grant
making in a way we can get some credible

908
01:26:30.360 --> 01:26:33.840
evidence and that's the controlled

909
01:26:35.000 --> 01:26:41.840
experiments okay so the leadership Cindy
Crosby Lara in these conversations with

910
01:26:41.840 --> 01:26:48.639
Emily and me over a year we looking at
all the things that IMS is trying to do

911
01:26:48.639 --> 01:26:53.360
and they identify three key
priorities one is looking at the

912
01:26:53.360 --> 01:26:57.360
contributions of libraries to advance
child reading and Emily's going to talk

913
01:26:57.360 --> 01:27:02.159
a bit about
that the second one is looking at where

914
01:27:02.159 --> 01:27:08.320
the future of the museum sector is going
22 23 coming out of Co coming out of the

915
01:27:08.320 --> 01:27:11.840
social justice movements and we're
starting to look at some demographic

916
01:27:11.840 --> 01:27:17.800
shifts lots of things going on in this
sector what does that suggest for where

917
01:27:17.800 --> 01:27:21.679
that sector
going and then for our grant making

918
01:27:21.679 --> 01:27:25.480
particularly our competitive
discretionary Grant making

919
01:27:25.480 --> 01:27:31.920
what do we know about how Equitable it
might be and these three issues form the

920
01:27:31.920 --> 01:27:37.440
basis of learning agenda where we
dictate certain questions that we want

921
01:27:37.440 --> 01:27:42.320
answered with evidence we dictate the
methods for collecting those evidence

922
01:27:42.320 --> 01:27:46.119
and then the processes for trying to
disseminate the

923
01:27:46.119 --> 01:27:51.360
learning while that's going on we've got
a big plate and we've got some other

924
01:27:51.360 --> 01:27:55.400
stuff we've got Marissa and another one
of our colleagues Jake they're running

925
01:27:55.400 --> 01:27:59.719
our statistical
surveys you already heard today about

926
01:27:59.719 --> 01:28:03.840
the evaluation we were doing of covid
there's another evaluation that we're

927
01:28:03.840 --> 01:28:08.840
wrapping up now of our four Native
American native Hawaiian Grant programs

928
01:28:08.840 --> 01:28:12.080
and we're going to talk a little bit
about this Congressional mandate for

929
01:28:12.080 --> 01:28:16.719
imls to assess the needs of INF of the
country's uh infrastructure of the

930
01:28:16.719 --> 01:28:22.159
country's libraries and museums so
that's our portfolio within it we've got

931
01:28:22.159 --> 01:28:25.840
this
prioritized set of questions in our

932
01:28:25.840 --> 01:28:29.040
learning agenda that we're going to try
to collect any

933
01:28:29.040 --> 01:28:33.760
evidence course I go back with Cindy a
little bit a couple of years and we got

934
01:28:33.760 --> 01:28:38.119
to have a little coffee today I'm going
to just put her on the spot and ask

935
01:28:38.119 --> 01:28:42.239
Cindy if you might want to just put any
some observation about from your eyes

936
01:28:42.239 --> 01:28:45.960
the perspective of the acting director
about where the learning agenda is

937
01:28:45.960 --> 01:28:51.159
sitting in in imess
Vision um so first of all thank you Matt

938
01:28:51.159 --> 01:28:59.880
for calling on me uh that Dr Matt
teacher and Mentor um so when I think

939
01:28:59.880 --> 01:29:04.400
about the learning
agenda and what we what will come out of

940
01:29:04.400 --> 01:29:12.639
it um it is my hope that it will then
begin to shape some things in terms of

941
01:29:12.639 --> 01:29:20.000
uh some of the you know 22 we finished a
a strategic plan as Matt said and guess

942
01:29:20.000 --> 01:29:26.480
what in 26 we'll be ready to do another
one I know that seems so far off but not

943
01:29:26.480 --> 01:29:31.239
really um so I think that there's a lot
of it's a learning agenda so I think

944
01:29:31.239 --> 01:29:35.760
there will be a lot of learning that
will come from this that will inform

945
01:29:35.760 --> 01:29:43.080
that and I do think that it will shape
um our grant making in ways that maybe

946
01:29:43.080 --> 01:29:48.520
are uh different or discretionary Grant
making and ways that are different than

947
01:29:48.520 --> 01:29:55.400
they are now um and then I will say that
the child reading actually I cannot take

948
01:29:55.400 --> 01:30:00.840
any credit for that that was our former
director Crosby Kemper he had a real

949
01:30:00.840 --> 01:30:06.080
passion for this and I think it you know
we we already understand I think as

950
01:30:06.080 --> 01:30:13.199
Librarians that we play a seminal role
in literacy and but really being able to

951
01:30:13.199 --> 01:30:18.440
evidence it and then for us from a grant
making perspective thinking about the

952
01:30:18.440 --> 01:30:24.400
ways that we might invest in support of
libraries and their role in that reading

953
01:30:24.400 --> 01:30:30.400
ecosystem as we move forward is really
going to be something um that we'll be

954
01:30:30.400 --> 01:30:35.840
thinking about as we learn from these
different uh sort of sub research

955
01:30:35.840 --> 01:30:41.600
agendas of the larger learning
agenda thanks

956
01:30:43.600 --> 01:30:48.480
Cindy so I'm going to turn it over to
Emily and she's gonna talk to you about

957
01:30:48.480 --> 01:30:52.239
where we've been advancing with our
learning agenda topic around child

958
01:30:52.239 --> 01:30:55.239
reading

959
01:30:58.040 --> 01:31:03.360
um I'll also be talking about the status
of our infrastructure study so like any

960
01:31:03.360 --> 01:31:08.280
good thing o we have way more content on
our slides than we have time for so I'm

961
01:31:08.280 --> 01:31:14.360
going to zip through some of this pretty
quickly um but I did very intentionally

962
01:31:14.360 --> 01:31:19.639
leave a lot of content on the slides um
so that you could go back and look at it

963
01:31:19.639 --> 01:31:24.639
later I wanted to make sure it was
available um

964
01:31:24.639 --> 01:31:34.760
and uh ector loo para
Rapido um I'm GNA go fast really quickly

965
01:31:34.760 --> 01:31:41.159
I I am a I am a person who is Thoroughly
Midwestern I grew up in Northwest Iowa

966
01:31:41.159 --> 01:31:46.280
my parents and younger sister live in
Minnesota my older sister is in Missouri

967
01:31:46.280 --> 01:31:51.760
I currently
reside south of here in Chicago um but I

968
01:31:51.760 --> 01:31:58.480
cut my adult teeth here in
Wisconsin um undergrad graduate spent 10

969
01:31:58.480 --> 01:32:03.320
years working here including in this
building as a banquet chef and met my

970
01:32:03.320 --> 01:32:11.159
husband here um this very building yeah
um so when I found out that we were

971
01:32:11.159 --> 01:32:17.119
going to be here uh there was a lot of
excited yelling and also that there was

972
01:32:17.119 --> 01:32:20.920
an opportunity for me to think of a
great theme about Wisconsin or Milwaukee

973
01:32:20.920 --> 01:32:24.480
that I could incorporate in my slides
and I spent way more time that I needed

974
01:32:24.480 --> 01:32:28.080
to thinking about what I could
do

975
01:32:28.080 --> 01:32:33.000
and I say I'm thoroughly Midwestern
because out of all the states Wisconsin

976
01:32:33.000 --> 01:32:37.159
is my favorite um

977
01:32:39.199 --> 01:32:47.040
so we'll talk later
um so just to say um my Wisconsin slides

978
01:32:47.040 --> 01:32:52.920
as a data person are the most obvious
evidence I could find of myself being

979
01:32:52.920 --> 01:32:58.960
excited about the state of Wisconsin so
that if there is any kind of vote later

980
01:32:58.960 --> 01:33:07.000
SL superlative um it's G to be
me so uh we'll just you know go back to

981
01:33:07.000 --> 01:33:11.800
this first slide just in case you
wondered how I feel about Wisconsin and

982
01:33:11.800 --> 01:33:16.760
where we
are okay so let's get into child reading

983
01:33:16.760 --> 01:33:22.800
and less about me
um this particular piece of literature

984
01:33:22.800 --> 01:33:28.199
this is a piece of re search that is
public imls has issued it's available

985
01:33:28.199 --> 01:33:31.800
we've presented to KLA we've presented
to a couple of different folks we were

986
01:33:31.800 --> 01:33:37.800
at ala on this um it's out there this
this the purpose of this presentation is

987
01:33:37.800 --> 01:33:41.960
really just to make you aware of kind of
the Core Concepts that are in the paper

988
01:33:41.960 --> 01:33:46.239
and how you might be able to use some of
it when you're looking at your literacy

989
01:33:46.239 --> 01:33:49.880
programming so there's a bunch of
background here again I'm going to go

990
01:33:49.880 --> 01:33:55.480
through these slides pretty quickly um
basically just saying we are building

991
01:33:55.480 --> 01:34:01.520
this child research literature review on
some past meetings that we've had it was

992
01:34:01.520 --> 01:34:06.679
conducted by the American Institutes of
research um people who are way better at

993
01:34:06.679 --> 01:34:10.760
me with stats uh went out and did the
research and I just get to present on

994
01:34:10.760 --> 01:34:15.159
their interesting findings and what
we're really trying to understand in

995
01:34:15.159 --> 01:34:19.560
this paper what we brought to the
original concept of this paper is this

996
01:34:19.560 --> 01:34:24.520
idea that libraries have been wanting to
measure their impact on reading in

997
01:34:24.520 --> 01:34:29.719
particular for a long time but it's been
really hard to find a direct line

998
01:34:29.719 --> 01:34:35.000
between Library influence on reading and
reading skills and I'm not going to tell

999
01:34:35.000 --> 01:34:40.600
you anything that most of you don't
already know um but getting that direct

1000
01:34:40.600 --> 01:34:44.199
contribution trying to understand what
is it that libraries really do to help

1001
01:34:44.199 --> 01:34:50.239
with reading in particular is just so
hard to get to because if we look at

1002
01:34:50.239 --> 01:34:56.239
school scores and we try and map where
the library shows up there's so much

1003
01:34:56.239 --> 01:35:01.400
role that the library plays in informal
learning that isn't measured in what we

1004
01:35:01.400 --> 01:35:05.679
see in standardized tests so the
hypothesis that we're trying to work

1005
01:35:05.679 --> 01:35:11.119
with here is what are the things that
libraries really contribute to as a

1006
01:35:11.119 --> 01:35:15.239
significant factor when it comes to
child reading literacy so we're not

1007
01:35:15.239 --> 01:35:18.840
talking about financial literacy we're
not talking about adult literacy we're

1008
01:35:18.840 --> 01:35:24.880
just really looking at kind of the core
like kids learning how to read and

1009
01:35:24.880 --> 01:35:31.400
libraries we hear so often that people
love libraries and they learn to love to

1010
01:35:31.400 --> 01:35:36.639
read Because of libraries and so if
there's this potential if we can find

1011
01:35:36.639 --> 01:35:43.000
evidence that there's a that motivation
the concept of motivation and

1012
01:35:43.000 --> 01:35:47.480
engagement
influences how kids

1013
01:35:47.480 --> 01:35:54.440
read and we can find evidence that says
libraries are

1014
01:35:54.440 --> 01:36:00.320
motivators are are motivators they bring
motivation to the idea of reading then

1015
01:36:00.320 --> 01:36:05.440
maybe we can start to actually find
evidence that could say Li that could

1016
01:36:05.440 --> 01:36:10.960
help us tease out what that role
libraries play in the literacy space

1017
01:36:10.960 --> 01:36:14.760
it's not to say that libraries don't do
formal education it's not to say that

1018
01:36:14.760 --> 01:36:18.440
libraries don't do literacy in other
ways but we're looking at motivation as

1019
01:36:18.440 --> 01:36:23.800
like the measurement that we might be
able to actually pull out of this set

1020
01:36:23.800 --> 01:36:28.639
data and see if we can get to some
evidence so more stuff about the

1021
01:36:28.639 --> 01:36:32.360
research questions these are the
research questions paper looks at they

1022
01:36:32.360 --> 01:36:37.760
inform the um learning agenda as we have
it in place right now Lisa is doing an

1023
01:36:37.760 --> 01:36:42.199
outstanding job of keeping the current
reading research going so next year

1024
01:36:42.199 --> 01:36:45.960
we'll be able to share you share with
you the next iteration of research

1025
01:36:45.960 --> 01:36:49.719
that's come out of what we learned from
this paper and what we're setting up in

1026
01:36:49.719 --> 01:36:53.840
the learning agenda again this is just
the structure of the literature revie

1027
01:36:53.840 --> 01:37:01.920
that air did um it's really again we're
talking Under 12 years kids reading

1028
01:37:01.920 --> 01:37:07.440
books
um could be hard books mostly hard copy

1029
01:37:07.440 --> 01:37:13.280
books we'll touch a little bit on uh
Virtual Reading but we really aren't

1030
01:37:13.280 --> 01:37:17.639
we're trying again to just put
boundaries on something we could go

1031
01:37:17.639 --> 01:37:20.679
broad we could go way broader we all
know we could go way broader we're

1032
01:37:20.679 --> 01:37:24.320
trying to just put some boundaries on
one piece of it where we might be able

1033
01:37:24.320 --> 01:37:29.480
to see a high concentration of where
motivation is being

1034
01:37:29.480 --> 01:37:34.440
delivered and of course we all know that
there's not a lot of Library research

1035
01:37:34.440 --> 01:37:39.840
out there so the paper itself basically
goes through all of the evidence based

1036
01:37:39.840 --> 01:37:44.679
research where there has been some kind
of attempt to measure engagement and

1037
01:37:44.679 --> 01:37:50.360
some type of attempt to measure
engagement as it relates to literacy but

1038
01:37:50.360 --> 01:37:56.360
as you will not be surprised the library
literature out there is very anecdotal

1039
01:37:56.360 --> 01:38:00.000
um it's very story based case study
based so a lot of the evidence that we

1040
01:38:00.000 --> 01:38:06.679
did find even though it says motivation
is an important factor comes from

1041
01:38:06.679 --> 01:38:11.119
school-based uh research that said
you're going to see in the slides in a

1042
01:38:11.119 --> 01:38:15.400
couple of slides that um the motivation
activities that come out of this

1043
01:38:15.400 --> 01:38:20.159
school-based research are straight out
of what libraries do so there's a really

1044
01:38:20.159 --> 01:38:28.280
good it's not a onetoone um
research comparison but there's a lot

1045
01:38:28.280 --> 01:38:31.159
there's a lot of really good overlap in
terms of what we're looking at in the

1046
01:38:31.159 --> 01:38:37.239
studies that are out
there so first of all we start with this

1047
01:38:37.239 --> 01:38:45.800
idea is is does reading does motivation
influence child literacy and we didn't

1048
01:38:45.800 --> 01:38:50.199
try
to the the paper isn't about arguing yes

1049
01:38:50.199 --> 01:38:56.480
or no it's assuming it's starting with
evidence that says motivation

1050
01:38:56.480 --> 01:39:02.520
matters um and so we have a good basis
of research that's out there that talks

1051
01:39:02.520 --> 01:39:09.560
about why motivation can improve
literacy um and why engagement is

1052
01:39:09.560 --> 01:39:15.639
important why positive feelings about
reading is what can help someone who

1053
01:39:15.639 --> 01:39:20.159
knows how to read move from just knowing
how to read to wanting to read right

1054
01:39:20.159 --> 01:39:24.080
because we can all read instructions on
how to set up our mic microwave but no

1055
01:39:24.080 --> 01:39:29.719
one's going to do that by
choice hopefully

1056
01:39:29.719 --> 01:39:36.000
um so like that that trigger for moving
from I have to read something to I want

1057
01:39:36.000 --> 01:39:41.159
to read something is really that point
that's the point that we're looking at

1058
01:39:41.159 --> 01:39:48.239
here so the literature review looks at
four different ways that four different

1059
01:39:48.239 --> 01:39:54.639
core components of literacy instruction
literacy delivery

1060
01:39:54.639 --> 01:40:00.840
and it looks to see if there's proof of
um proof that motivation when

1061
01:40:00.840 --> 01:40:06.880
incorporated into any of these four
Concepts improves reading literacy and

1062
01:40:06.880 --> 01:40:10.520
so we're really looking at that line
between motivation

1063
01:40:10.520 --> 01:40:16.760
engagement and does it does it show up
when does motivation matter when we're

1064
01:40:16.760 --> 01:40:24.280
trying to get kids to read hey the
findings if you haven't seen the bronze

1065
01:40:24.280 --> 01:40:31.719
FS find it is that a bingo card thing
should be oh should be he's on the river

1066
01:40:31.719 --> 01:40:37.520
we love the fs in milwauke Milwaukee
loves F okay so long story short

1067
01:40:37.520 --> 01:40:41.760
motivation matters it does matter
getting and again this shouldn't

1068
01:40:41.760 --> 01:40:46.719
surprise you you're in the field but
getting kids to want to read makes them

1069
01:40:46.719 --> 01:40:53.639
better
readers it's it takes a want to read

1070
01:40:53.639 --> 01:40:59.560
combined with literacy development to
really see reading performance change so

1071
01:40:59.560 --> 01:41:03.800
you're not just going to sit in school
and tell kids that T and H make a th

1072
01:41:03.800 --> 01:41:08.280
sound and those kids are going to go on
and be excellent readers you need

1073
01:41:08.280 --> 01:41:13.280
something that's going to motivate them
to want to read about things that have

1074
01:41:13.280 --> 01:41:20.360
the in the sentence that was a terrible
example sorry um also this one's super

1075
01:41:20.360 --> 01:41:24.719
interesting so you know there are some
hypothesis out there that books you get

1076
01:41:24.719 --> 01:41:28.800
more books to kids kids are going to
read more books if I have a table of 100

1077
01:41:28.800 --> 01:41:33.800
books in front of
me and those books alone are the only

1078
01:41:33.800 --> 01:41:39.320
thing that I have that help me learn how
to read or want to read that that would

1079
01:41:39.320 --> 01:41:43.159
be enough for me to become an Avid
Reader and what the research says is no

1080
01:41:43.159 --> 01:41:49.599
that's not true you need motivational
principles Incorporated with those books

1081
01:41:49.599 --> 01:41:56.840
because books alone cannot get a child
into competent not competent they can't

1082
01:41:56.840 --> 01:42:02.159
move them move the needle the way we
want them to so everything really is

1083
01:42:02.159 --> 01:42:06.599
integrated again this should be
self-evident to what you're

1084
01:42:06.599 --> 01:42:12.199
doing it makes a lot of sense that one
activity on its own standing alone

1085
01:42:12.199 --> 01:42:16.440
wouldn't help us get more literate
readers but I am just so fascinated by

1086
01:42:16.440 --> 01:42:21.880
how the motivation shows up in these
things so I'm just going to touch really

1087
01:42:21.880 --> 01:42:27.440
briefly on these four princi principles
content-based approaches are the idea

1088
01:42:27.440 --> 01:42:33.920
again that you are um putting an English
book in front of a child and you're

1089
01:42:33.920 --> 01:42:37.040
having them read from a textbook right
that's the content that you're having

1090
01:42:37.040 --> 01:42:41.480
them read the read of I don't know what
happened to my slides here they look

1091
01:42:41.480 --> 01:42:47.960
better anyway sorry um again and these
are also a lot of non-library studies

1092
01:42:47.960 --> 01:42:53.880
but this idea that you're putting
narrative content tied to

1093
01:42:53.880 --> 01:43:02.000
reading instruction
content is very compelling and obvious

1094
01:43:02.000 --> 01:43:08.040
if you have a book about a wizard and
you're trying to help kids learn how to

1095
01:43:08.040 --> 01:43:13.280
read and they're interested in Wizards
you're going to want to pair that

1096
01:43:13.280 --> 01:43:17.679
phonics based learning with information
about Wizardry and that will help

1097
01:43:17.679 --> 01:43:22.960
increase reading comprehension so they
will understand that when they see the

1098
01:43:22.960 --> 01:43:29.599
word word the it could be the broom or
the magic ball or the witch's hat um but

1099
01:43:29.599 --> 01:43:35.599
they will connect how to sayth they will
connect whatthe means when they're doing

1100
01:43:35.599 --> 01:43:38.480
it surrounded by things that they're
interested

1101
01:43:38.480 --> 01:43:44.719
in the second
piece does any of this all of this is

1102
01:43:44.719 --> 01:43:50.880
Library all of this is Library the
second piece is having practices

1103
01:43:50.880 --> 01:43:56.080
activities integrated with practices
these are all things that you all do but

1104
01:43:56.080 --> 01:44:03.480
just having it's like having wraparound
activities that

1105
01:44:03.480 --> 01:44:10.239
reinforce reading and literacy
concepts are what help informal

1106
01:44:10.239 --> 01:44:15.400
instruction move kids from just reading
to want to read um and if you think

1107
01:44:15.400 --> 01:44:20.280
about it like there are so much that
libraries do in this space with kids

1108
01:44:20.280 --> 01:44:25.000
with families that
to pair it with a

1109
01:44:25.000 --> 01:44:30.719
school project a program literacy goals
um where the library is bringing this

1110
01:44:30.719 --> 01:44:34.800
and the schools bring in the formal
instruction like that's just such a

1111
01:44:34.800 --> 01:44:39.280
powerful way to help to help with
literacy

1112
01:44:39.280 --> 01:44:45.400
goals um supportive resources
literacy reading comprehension reading

1113
01:44:45.400 --> 01:44:49.760
performance gets better when you have
other types of resources available the

1114
01:44:49.760 --> 01:44:53.520
the reading to dogs of course like that
one shows up time and time again in

1115
01:44:53.520 --> 01:44:59.040
evidence um things spaces we have a lot
of movement around helping libraries

1116
01:44:59.040 --> 01:45:04.840
reinvent spaces so that books are more
logically accessible to kids and not

1117
01:45:04.840 --> 01:45:10.119
tied to the you know tied to the the
system of organization that we might

1118
01:45:10.119 --> 01:45:15.560
have been formally trained in um I'm not
going to T touch technology with a 5-

1119
01:45:15.560 --> 01:45:22.280
foot pool that's mixed evid 10 foot pool
30 foot pool um that's mixed evidence

1120
01:45:22.280 --> 01:45:28.159
Tech in some instances helps with
accessibility and helps kids get closer

1121
01:45:28.159 --> 01:45:31.520
to engaged reading but in but we also
know there's evidence out there that

1122
01:45:31.520 --> 01:45:35.920
says it can really harm engaged reading
so when you look at the paper and you

1123
01:45:35.920 --> 01:45:39.599
see the examples here you're going to
see some mixed results I should also say

1124
01:45:39.599 --> 01:45:43.080
the evidence that they lay out in the
paper

1125
01:45:43.080 --> 01:45:48.000
um it's there are some areas that are
stronger than others and I think that's

1126
01:45:48.000 --> 01:45:51.599
also really interesting too where you
might say like oh I see really clear

1127
01:45:51.599 --> 01:45:57.480
evidence in the instructional content
piece but um we didn't shy away from

1128
01:45:57.480 --> 01:46:02.360
talking about things that were
interesting and compelling but not fully

1129
01:46:02.360 --> 01:46:05.880
developed because if we had to wait on
that we never would have been able to

1130
01:46:05.880 --> 01:46:11.199
get this paper out the
door um Family

1131
01:46:11.199 --> 01:46:17.119
engagement if you haven't been screaming
family engagement in your head by now

1132
01:46:17.119 --> 01:46:22.320
um this you know will it should lead you
to do that where family engagement of

1133
01:46:22.320 --> 01:46:27.360
course is core to helping improve
reading comprehension help improve kids

1134
01:46:27.360 --> 01:46:33.159
learning how to
read this is an area that in in kind of

1135
01:46:33.159 --> 01:46:37.040
reflection of how the lit review came
out and in reflection of what you'll see

1136
01:46:37.040 --> 01:46:44.280
in the learning questions it is
so critical that we figure out how to

1137
01:46:44.280 --> 01:46:49.119
incorporate the role of family or
caretakers in the reading space in

1138
01:46:49.119 --> 01:46:54.840
research because we can't you can't
separate those two

1139
01:46:55.159 --> 01:47:02.000
um if a family is not involved the kid
is not you know it's it's rare to see a

1140
01:47:02.000 --> 01:47:08.320
kid learn how to love reading or see
have strong reading skills but that's

1141
01:47:08.320 --> 01:47:12.400
almost its
own path of research so we're trying to

1142
01:47:12.400 --> 01:47:16.159
figure out how we can explore that in
the context of

1143
01:47:16.159 --> 01:47:20.639
motivation you know in some instances
there are questions where are family

1144
01:47:20.639 --> 01:47:25.880
stronger contributors to literacy than
libraries or schools and um you know we

1145
01:47:25.880 --> 01:47:30.960
certainly don't want to find ourselves
down that path of of needing to make an

1146
01:47:30.960 --> 01:47:34.040
argument for one or the other because
it's really when we think about the

1147
01:47:34.040 --> 01:47:37.639
literacy ecosystem it's a whole and
that's what we're finding from the

1148
01:47:37.639 --> 01:47:42.080
research it's a whole it's not one thing
that is the winner it's it's an

1149
01:47:42.080 --> 01:47:46.480
integrated
contribution so I'm going to stop here I

1150
01:47:46.480 --> 01:47:50.560
was going to do a round table discussion
I'm going to keep going though because I

1151
01:47:50.560 --> 01:47:55.000
think talking about the infrastructure
study study is going to be also very

1152
01:47:55.000 --> 01:48:01.520
interesting for you um but I do want to
prompt you to just think about what

1153
01:48:01.520 --> 01:48:07.760
about this research resonates with you
you all are on you are you are entities

1154
01:48:07.760 --> 01:48:13.280
that are helping direct L literacy
efforts in your States you're hearing

1155
01:48:13.280 --> 01:48:17.199
from your libraries about the challenges
they're facing around child literacy

1156
01:48:17.199 --> 01:48:21.880
you're hearing about what libraries are
having to do in a post-pandemic world

1157
01:48:21.880 --> 01:48:27.000
when it terms when it comes to trying to
help promote reading um you know just

1158
01:48:27.000 --> 01:48:30.560
think about this food for thought I
would love to hear afterwards or if we

1159
01:48:30.560 --> 01:48:35.199
have time what some of your thoughts are
about this um especially as we continue

1160
01:48:35.199 --> 01:48:41.360
to invest in literacy I know it's not I
know that literacy isn't the hottest of

1161
01:48:41.360 --> 01:48:46.960
Hot Topics right now but it's so core
and so

1162
01:48:46.960 --> 01:48:52.199
critical to what
libraries Provide support for in their

1163
01:48:52.199 --> 01:48:56.199
community that sometimes just making
sure we're backing up what we already

1164
01:48:56.199 --> 01:49:01.920
know to be true um is a good it's a good
priority to have um so this is really

1165
01:49:01.920 --> 01:49:06.560
great research we're really excited
about it we're going to have like I said

1166
01:49:06.560 --> 01:49:13.719
more information coming out next year
um these are the actual learning agenda

1167
01:49:13.719 --> 01:49:19.119
child research questions Matt did you
want to say anything specific about them

1168
01:49:19.119 --> 01:49:24.520
okay
um it gets you know it's definitely a

1169
01:49:24.520 --> 01:49:29.360
little wonky when it comes to now we're
talking about research and what that

1170
01:49:29.360 --> 01:49:33.920
entails um one thing that I think is
really compelling in these in this

1171
01:49:33.920 --> 01:49:40.239
question is understanding the role of
the library as a literacy contributor in

1172
01:49:40.239 --> 01:49:46.040
the literacy ecosystem so instead of
starting from the point of what is a

1173
01:49:46.040 --> 01:49:51.000
library what do Partnerships look like
what do literacy Partnerships look like

1174
01:49:51.000 --> 01:49:53.760
we're actually taking a step back
further and we're saying all right let's

1175
01:49:53.760 --> 01:49:58.280
look at the whole literacy ecosystem in
a community what is the contribution

1176
01:49:58.280 --> 01:50:03.480
that a library makes in the literacy
system literally C ecosystem we have

1177
01:50:03.480 --> 01:50:08.560
other entities out there like the Dolly
Parton Imagination Library we have

1178
01:50:08.560 --> 01:50:14.520
Barber Shop books and the laundromat um
laundromats and books uh we have the

1179
01:50:14.520 --> 01:50:19.960
schools we have other nonprofits that
have mentorships or um after school

1180
01:50:19.960 --> 01:50:24.920
tutoring that are contributing to
literacy so we look at all of those what

1181
01:50:24.920 --> 01:50:29.159
is the you know what is what does the
library look

1182
01:50:29.159 --> 01:50:34.560
like um and you know hopefully we'll
have some really interesting answers to

1183
01:50:34.560 --> 01:50:41.239
bring with you next year so um come
back in a year and we'll tell

1184
01:50:41.239 --> 01:50:46.920
you so you can get this online um we'll
make sure that we send the link around

1185
01:50:46.920 --> 01:50:51.599
afterwards take a look at it what's
really awesome about the paper is that

1186
01:50:51.599 --> 01:50:56.199
these are this is for for you to take
ideas on things that you could do you

1187
01:50:56.199 --> 01:51:00.760
know encourage other libraries in your
states to take take on or if you're

1188
01:51:00.760 --> 01:51:05.280
looking to partner with someone um you
know take a look at what you know

1189
01:51:05.280 --> 01:51:08.719
libraries offer what you might offer for
literacy and

1190
01:51:08.719 --> 01:51:15.320
then you know see if you can find ways
to strengthen that literacy activity in

1191
01:51:15.320 --> 01:51:21.560
your
community okay now we're going to do a

1192
01:51:21.560 --> 01:51:27.400
90 degree turn and we're g to talk about
buildings infrastructure before we do

1193
01:51:27.400 --> 01:51:33.679
that does anybody have any questions or
comments that what Emily just Shar with

1194
01:51:33.679 --> 01:51:36.000
child

1195
01:51:36.400 --> 01:51:43.480
reading Qui questions or comments does
this work is it working yeah before we

1196
01:51:43.480 --> 01:51:48.119
move on to infrastructure
study anything that anybody wants to

1197
01:51:48.119 --> 01:51:52.920
share about what you've just reflected
on listening to Emily talk about child

1198
01:51:52.920 --> 01:51:57.480
reading or similar if we were to come
back a year from now and talk about

1199
01:51:57.480 --> 01:52:03.159
child reading is there anything that
you'd be interested in learning more

1200
01:52:05.320 --> 01:52:13.199
about at
three EOS definitely want more info okay

1201
01:52:13.199 --> 01:52:18.280
yeah just to give people a little bit of
a metaphor em Emily was touching on it

1202
01:52:18.280 --> 01:52:22.560
so rather than starting as the library
is the subject we really want to talk

1203
01:52:22.560 --> 01:52:26.520
talk about the child and the family and
think about their journey in their

1204
01:52:26.520 --> 01:52:31.480
Community who goes to the library to
learn to read who goes elsewhere what

1205
01:52:31.480 --> 01:52:35.760
does that how does that Journey fa how
do the kids Fair based on who they're

1206
01:52:35.760 --> 01:52:40.159
interacting in other circumstances and
that's really what that whole ecosystem

1207
01:52:40.159 --> 01:52:48.920
piece is intended to help
explore i j forward that to our

1208
01:52:48.920 --> 01:52:53.880
Consultants I think that lii

1209
01:53:02.280 --> 01:53:05.280
I

1210
01:53:05.520 --> 01:53:08.520
add

1211
01:53:13.880 --> 01:53:21.000
me yeah yeah thank
you Ben me again

1212
01:53:21.000 --> 01:53:26.280
uh I I assume in this in the context of
the study when you talk about libraries

1213
01:53:26.280 --> 01:53:30.000
you're really zeroing in on public
libraries and that school libraries will

1214
01:53:30.000 --> 01:53:35.000
be part of the larger reading ecosystem
okay public libraries yeah yeah

1215
01:53:35.000 --> 01:53:39.960
yeah I we we know School libraries are
contributors they're a little bit harder

1216
01:53:39.960 --> 01:53:47.079
structure to tackle so we started on
the okay so for followup you know Emily

1217
01:53:47.079 --> 01:53:52.840
and others are around for office hours
we all around today and tomorrow in the

1218
01:53:52.840 --> 01:53:57.960
interest of time now as I look at Terry
we're going to move on to infrastructure

1219
01:53:57.960 --> 01:54:02.040
study one more Lindsay Lindsay you want
to do oh we got one

1220
01:54:02.040 --> 01:54:06.880
more um my question might will be on the
scope of what you're looking at I just

1221
01:54:06.880 --> 01:54:11.159
know that Public Library SP

1222
01:54:31.679 --> 01:54:36.079
yeah
yeah yeah and the summer reading they

1223
01:54:36.079 --> 01:54:39.679
had the summer reading they focused on
that they got evidence from around

1224
01:54:39.679 --> 01:54:43.719
motivation was in schools and not in
libraries and that's really interesting

1225
01:54:43.719 --> 01:54:48.920
because we know libraries measure summer
reading so um how can we get to that

1226
01:54:48.920 --> 01:54:54.040
data
better okay I'm going to move on to

1227
01:54:54.040 --> 01:54:57.040
infrastructure

1228
01:54:57.159 --> 01:55:04.480
um goals of research goals of a study
are always painful to read on paper um

1229
01:55:04.480 --> 01:55:10.760
this is me in 2010 doing the polar pron
Madison or 2008 okay so goals of the

1230
01:55:10.760 --> 01:55:16.000
study this is a congressionally mandated
study looking at the state of

1231
01:55:16.000 --> 01:55:21.679
infastructure
of public libraries and museums across

1232
01:55:21.679 --> 01:55:26.960
the United States
um these the goals that we have outlined

1233
01:55:26.960 --> 01:55:32.800
here are intended to inform Congress
based on what Congress told us they

1234
01:55:32.800 --> 01:55:40.119
wanted to learn so I want to make really
clear that this is like a gaps and needs

1235
01:55:40.119 --> 01:55:48.560
type exercise that goes back to our
funders um and then what comes after

1236
01:55:48.560 --> 01:55:54.760
that is TBD so this is really the we are
at the very front edge of trying to get

1237
01:55:54.760 --> 01:55:58.719
our arms around the national
infrastructure needs of libraries and

1238
01:55:58.719 --> 01:56:01.639
museums across the United States and we
know that they're

1239
01:56:01.639 --> 01:56:06.159
there
um these are the research questions

1240
01:56:06.159 --> 01:56:12.639
themselves that are directing the study
the study is about eight months in it's

1241
01:56:12.639 --> 01:56:19.320
a 16 to 18 month study um so these
questions have been vetted this is what

1242
01:56:19.320 --> 01:56:22.520
we're working on when we're going out
and doing the research I'll talk about

1243
01:56:22.520 --> 01:56:26.880
what each other the research elements
look like for those of you who were on

1244
01:56:26.880 --> 01:56:32.360
this end of the room and have feelings
of a time when there was funding for

1245
01:56:32.360 --> 01:56:37.599
infrastructure um infrastructure funds
and for those of you who know that you

1246
01:56:37.599 --> 01:56:42.400
have construction needs that libraries
come to you and ask you about um there

1247
01:56:42.400 --> 01:56:48.400
are various ways we're trying to get to
as much data as we can in this time

1248
01:56:48.400 --> 01:56:52.239
frame but really there are a couple of
things that are important to call out

1249
01:56:52.239 --> 01:56:57.280
out here one is that we're looking at
areas of need which are rural

1250
01:56:57.280 --> 01:57:02.239
underserved and disaster prone
communities um Congress directed us

1251
01:57:02.239 --> 01:57:06.520
specifically to focus on those three key
indicators when we tried to look at what

1252
01:57:06.520 --> 01:57:13.040
infrastructure needs were uh in those
facets um ultimately it's kind of

1253
01:57:13.040 --> 01:57:19.960
everywhere like if they're underserved
communities in cities disas you know

1254
01:57:19.960 --> 01:57:22.719
everyone's feeling some kind of
effective climate change

1255
01:57:22.719 --> 01:57:28.960
right now so um for the sake
of people maybe being concerned that

1256
01:57:28.960 --> 01:57:32.320
they might be excluded from the study
more or less this is going to cover most

1257
01:57:32.320 --> 01:57:36.679
of the United States and we're just
focusing on a couple of areas that um we

1258
01:57:36.679 --> 01:57:42.960
know put physical buildings at higher
risk of either being under repair at

1259
01:57:42.960 --> 01:57:48.440
risk of um you know collections being at
risk

1260
01:57:49.280 --> 01:57:52.840
etc for those of you that like
Congressional language

1261
01:57:52.840 --> 01:57:58.760
I highlighted uh the Senate language
that says you got to do this study this

1262
01:57:58.760 --> 01:58:03.719
is the house language that says you got
to do a study um so we're doing it there

1263
01:58:03.719 --> 01:58:09.119
is a another report if you hear tell of
this being done by the GAO they have

1264
01:58:09.119 --> 01:58:13.679
almost the exact same language as come
out of the of both the house and the

1265
01:58:13.679 --> 01:58:19.440
Senate um we are coordinating with GAO I
like to say we are both on the same

1266
01:58:19.440 --> 01:58:22.440
dance floor and we're just making sure
that we don't bump into each each other

1267
01:58:22.440 --> 01:58:26.360
as we're out there doing research so GAO
is going to have some information that

1268
01:58:26.360 --> 01:58:29.480
they're going to publish there's going
to be information we're going to publish

1269
01:58:29.480 --> 01:58:33.960
um and I think it the two reports
combined are really going to tell us

1270
01:58:33.960 --> 01:58:39.320
this huge story about infrastructure
needs uh

1271
01:58:39.320 --> 01:58:45.719
imls and under the direction of our
fearless leader Matt um are overseeing

1272
01:58:45.719 --> 01:58:50.320
the project um we're working on it in
collaboration with basically every other

1273
01:58:50.320 --> 01:58:55.480
office at imls and then we have a a
research contractor that we've hired

1274
01:58:55.480 --> 01:59:00.520
called fed writers who are bringing on a
lot of the Staffing that we need to be

1275
01:59:00.520 --> 01:59:06.320
able to do this research
well um I just get so excited talking

1276
01:59:06.320 --> 01:59:10.599
about data
collection um and this is my husband and

1277
01:59:10.599 --> 01:59:16.320
this is when we went to a Packers game
if you couldn't tell um we have we have

1278
01:59:16.320 --> 01:59:22.480
a whole host of researches going on with
this report where um we're really trying

1279
01:59:22.480 --> 01:59:27.320
to make sure we know we can't go to
every state and site and location in the

1280
01:59:27.320 --> 01:59:31.840
United States um and so we're trying to
make sure we get as much coverage about

1281
01:59:31.840 --> 01:59:35.960
infrastructure needs as we can so we
have secondary data where we're doing

1282
01:59:35.960 --> 01:59:39.760
lint reviews we're looking at
administrative data um and then we have

1283
01:59:39.760 --> 01:59:43.560
primary research where we're going out
and doing interviews and facility sites

1284
01:59:43.560 --> 01:59:47.040
and the one thing I want to really make
sure that we we're integrating all the

1285
01:59:47.040 --> 01:59:50.320
data that's what this says we're doing
interviews these are the people that

1286
01:59:50.320 --> 01:59:55.480
we're interviewing we'll eventually be
able to share that more data about that

1287
01:59:55.480 --> 01:59:59.800
this is the information that no one has
yet seen so you're welcome hot off the

1288
01:59:59.800 --> 02:00:04.320
presses um these are the 10 library
locations where we are going to be

1289
02:00:04.320 --> 02:00:08.800
sending Engineers on site to do a
facility condition site assessment these

1290
02:00:08.800 --> 02:00:14.320
are going to help inform case studies
that come out of the report so um

1291
02:00:14.320 --> 02:00:18.320
Missouri Louisiana North Carolina
Colorado Alaska Maryland Texas Michigan

1292
02:00:18.320 --> 02:00:22.840
Oklahoma Kentucky and New Jersey
congratulations we got an engineer come

1293
02:00:22.840 --> 02:00:28.679
into your state um and this is new data
that we're going to be collecting we

1294
02:00:28.679 --> 02:00:31.719
know that there are so many different
types of libraries out there and so many

1295
02:00:31.719 --> 02:00:34.000
libraries that would love to have
someone come and do an assessment of

1296
02:00:34.000 --> 02:00:38.119
their buildings what we tried to make
sure is that we had diversity in the

1297
02:00:38.119 --> 02:00:44.639
types of governance structure of um
public libraries um the rur the

1298
02:00:44.639 --> 02:00:49.119
urbanicity and we also wanted to make
sure they met one of those criteria

1299
02:00:49.119 --> 02:00:54.800
around underserved um or disaster
so we're really trying to make sure we

1300
02:00:54.800 --> 02:01:00.320
take into account as much diversity in
these 10 sites as possible

1301
02:01:00.320 --> 02:01:04.719
um and we're going to be taking the data
from those sites rolling it up in

1302
02:01:04.719 --> 02:01:10.079
Aggregate and talking about some giving
some context um about those findings but

1303
02:01:10.079 --> 02:01:15.000
I want to go back here to the um things
that we're doing again like it's this is

1304
02:01:15.000 --> 02:01:18.960
one of many things that we're doing so
the sites are the exciting piece for

1305
02:01:18.960 --> 02:01:23.880
sure um but we are doing what we can to
not not miss all of the other important

1306
02:01:23.880 --> 02:01:28.320
places that we can get infrastructure
data because I bet that you probably can

1307
02:01:28.320 --> 02:01:32.040
think of a hundred libraries off the top
of your head that need help with their

1308
02:01:32.040 --> 02:01:36.000
buildings um we've even talked about it
with allowable cost today so we know

1309
02:01:36.000 --> 02:01:40.480
that there is a much greater need than
just going to 10 sites across the United

1310
02:01:40.480 --> 02:01:45.480
States this is our timeline I talked
about it um in

1311
02:01:45.480 --> 02:01:49.880
brief wait for next spring that's when
we're going to start bringing out some

1312
02:01:49.880 --> 02:01:55.480
of our results um there's a whole host
of activities that are going on between

1313
02:01:55.480 --> 02:01:59.880
now and then that are around data
collection analysis report review all

1314
02:01:59.880 --> 02:02:04.239
those fun things that go into issuing a
report

1315
02:02:04.239 --> 02:02:09.920
um and if this is not proof even more
proof that I am Wisconsin's number one

1316
02:02:09.920 --> 02:02:16.199
fan um my husband and I have a beautiful
daughter Esther who's about to turn one

1317
02:02:16.199 --> 02:02:23.840
uh she is our newest little Wisconsin
fan um we took this this summer and I'm

1318
02:02:23.840 --> 02:02:30.760
really hoping that I win the prize for
the most excited person to be here today

1319
02:02:30.760 --> 02:02:35.079
these are all the questions that I know
you're thinking about and so there are

1320
02:02:35.079 --> 02:02:39.280
the answers for you um so let's not ask
any of those and we can get them out of

1321
02:02:39.280 --> 02:02:43.520
the way and we have a couple minutes for
questions from the

1322
02:02:44.280 --> 02:02:48.520
audience or online

1323
02:03:17.119 --> 02:03:20.119
conru

1324
02:03:30.079 --> 02:03:35.520
so we looked do do you want to start you
start you're in a roll okay all right um

1325
02:03:35.520 --> 02:03:41.119
so we started with the criteria of under
sered disaster prone and Rural um

1326
02:03:41.119 --> 02:03:45.760
Atlantic City is you know right on the
disaster

1327
02:03:45.760 --> 02:03:50.559
prone right they're significantly
disaster prone underserved and

1328
02:03:50.559 --> 02:03:56.480
underserved um
and so so what our researchers did was

1329
02:03:56.480 --> 02:03:59.920
they pulled the list of all the
libraries in the United States they

1330
02:03:59.920 --> 02:04:04.800
applied those criteria so they winnowed
the list down and then from that

1331
02:04:04.800 --> 02:04:11.119
criteria they they developed a rubric of
looking at again the diversity in

1332
02:04:11.119 --> 02:04:17.920
governance structure um and
then Geographic

1333
02:04:17.920 --> 02:04:25.199
diversity um and from that they
started selecting the pool of libraries

1334
02:04:25.199 --> 02:04:32.360
um we didn't look at other factors like
past Awards we didn't look at um

1335
02:04:32.360 --> 02:04:37.239
other contributors because we wanted we
knew that there was going to be a big

1336
02:04:37.239 --> 02:04:43.719
range in some of these buildings are new
right that doesn't mean there aren't

1337
02:04:43.719 --> 02:04:48.719
needs I lived in a 2008 townhouse for a
while like there's a lot more needs in

1338
02:04:48.719 --> 02:04:52.239
that house than the 100-year-old house
sometimes

1339
02:04:52.239 --> 02:04:54.520
right so it doesn't mean that a newer
building doesn't need something it

1340
02:04:54.520 --> 02:04:57.679
doesn't mean because they might have
money and they might be able to talk

1341
02:04:57.679 --> 02:05:02.199
about how they're prioritizing
investment for that um so it really was

1342
02:05:02.199 --> 02:05:05.800
around diversity um but you know
certainly if there are things that you

1343
02:05:05.800 --> 02:05:10.280
want
to we can talk later if you want

1344
02:05:10.280 --> 02:05:19.840
um we didn't we did intentionally did
not try to account for things yeah yeah

1345
02:05:21.960 --> 02:05:24.639
is this on

1346
02:05:29.960 --> 02:05:33.920
yeah yes yeah you got

1347
02:05:43.159 --> 02:05:48.559
it
yes we we are and the folks at GAO are

1348
02:05:48.559 --> 02:05:52.559
interested as well yeah yeah we're
looking at so so on the administrative

1349
02:05:52.559 --> 02:05:58.119
data side what we're looking at is Grant
dollars that would go towards

1350
02:05:58.119 --> 02:06:02.679
infrastructure and then
seeing how much of that goes to

1351
02:06:02.679 --> 02:06:07.239
libraries or museums and then seeing
what kinds of funding libraries and

1352
02:06:07.239 --> 02:06:14.400
museums need F FCC of course has its
little asteris of you know big old eay

1353
02:06:14.400 --> 02:06:20.440
over here um and then we're also looking
at imls data because what I was thinking

1354
02:06:20.440 --> 02:06:24.480
about when we were looking at the allow
cost slides infrastructure construction

1355
02:06:24.480 --> 02:06:27.599
is part of infrastructure but there
might be parts of

1356
02:06:27.599 --> 02:06:32.760
infrastructure that are not construction
that we might be able to parse out with

1357
02:06:32.760 --> 02:06:38.880
an imals data especially within covid
whoever asked the co question um to see

1358
02:06:38.880 --> 02:06:44.800
like where where we have showed up as I
aess in the fringes of the

1359
02:06:44.800 --> 02:06:50.280
infrastructure space okay Emily dena's
got the question that's on everybody's

1360
02:06:50.280 --> 02:06:53.960
mind I'm going to ask her if she'll ask
it

1361
02:06:53.960 --> 02:06:59.000
again and it's it's probably a dumb
question but how will the research be

1362
02:06:59.000 --> 02:07:04.559
used um I think we are hoping in
Kentucky that some of the money could be

1363
02:07:04.559 --> 02:07:09.079
used for some of these infrastructure
and construction projects we do

1364
02:07:09.079 --> 02:07:16.320
administer a construction Grant through
State funding but we're finding that our

1365
02:07:16.320 --> 02:07:21.760
legislator doesn't want to open up the
purse strings on that as much so we're

1366
02:07:21.760 --> 02:07:26.119
looking for other sources I'm gonna let
the big boss answer that

1367
02:07:26.119 --> 02:07:32.400
one first thing I'm going to tell you is
our principal client is Congress they

1368
02:07:32.400 --> 02:07:38.520
the ones who requested the analysis
done and we're going to stand by the

1369
02:07:38.520 --> 02:07:44.599
science we don't want any perception
that the evidence that we have collected

1370
02:07:44.599 --> 02:07:52.520
and analyzed is biased by any
preconceptions by any uh ideological

1371
02:07:52.520 --> 02:07:57.000
objectives the second piece is we're
going to make it

1372
02:07:57.000 --> 02:08:03.520
accessible and maximize utilization by
other audiences outside of Congress we

1373
02:08:03.520 --> 02:08:10.280
are hoping that come next summer when
ala has its annual meeting for instance

1374
02:08:10.280 --> 02:08:15.119
that we will be there and presenting the
findings the third piece as we are

1375
02:08:15.119 --> 02:08:21.159
talking to the White House and Congress
right now we are in our own agency's

1376
02:08:21.159 --> 02:08:25.559
interest interest of being worried about
unfunded mandates we are very much

1377
02:08:25.559 --> 02:08:31.719
talking about what the study itself can
answer and why there'll be different

1378
02:08:31.719 --> 02:08:37.000
additional demands for follow-up
research the last part is in terms of

1379
02:08:37.000 --> 02:08:42.159
making it accessible is we hope to be
making the reporting data in available

1380
02:08:42.159 --> 02:08:48.040
in multiple ways including trying to
make sure that when GAO releases its

1381
02:08:48.040 --> 02:08:53.440
report that the two reports will be able
to read well together

1382
02:08:53.840 --> 02:08:56.079
well

1383
02:08:56.639 --> 02:09:01.280
said okay
any all right oh we have one last

1384
02:09:01.280 --> 02:09:06.000
question one last question and then
we'll wrap it up

1385
02:09:26.199 --> 02:09:34.079
working on the working on the what the I
didn't hear you sorry it's the echo

1386
02:09:47.239 --> 02:09:51.719
is oh okay

1387
02:10:07.880 --> 02:10:15.440
yeah I mean yes let's talk um I
haven't I haven't come across that or I

1388
02:10:15.440 --> 02:10:20.239
don't think our research team has come
across that group yet um it's a that's a

1389
02:10:20.239 --> 02:10:23.320
really interesting concept

1390
02:10:23.360 --> 02:10:28.040
um we haven't talked about Federal
versus state level construction

1391
02:10:28.040 --> 02:10:33.079
comparisons like we're really looking at
Federal level right now but um like the

1392
02:10:33.079 --> 02:10:37.920
mountain of information we expect to get
in the data collection portion of the

1393
02:10:37.920 --> 02:10:44.440
study it's going to inform any other
research that we do down the road so um

1394
02:10:44.440 --> 02:10:48.760
even if that's not something that fits
now like I think it's good to know

1395
02:10:48.760 --> 02:10:54.639
everything that's out there so thank you
Shameless plug for office hours later

1396
02:10:54.639 --> 02:11:02.079
we'll be there if you have other
questions thank you team Gran thank you

1397
02:11:05.199 --> 02:11:09.559
Emily rockar than

1398
02:11:09.760 --> 02:11:14.520
you okay Matt and I have a challenge
which is we're going to take our

1399
02:11:14.520 --> 02:11:20.079
15minute presentation and see if we can
do it in eight Matt are you up for the

1400
02:11:20.079 --> 02:11:23.559
challenge yeah
let's do it I would be betting against

1401
02:11:23.559 --> 02:11:28.040
me but go ahead okay Matt's gonna start
us off do you want to stand here what

1402
02:11:28.040 --> 02:11:32.840
are we going to do yeah sure

1403
02:11:33.280 --> 02:11:40.920
okay so you know little bit after the
dinosaurs kind of expired I joined IM

1404
02:11:40.920 --> 02:11:50.400
mes Karen was around sorry Karen um but
for four 14 for 14 years ago we were in

1405
02:11:50.400 --> 02:11:57.679
Baltimore and we were talking about how
can we tell a story a better story of

1406
02:11:57.679 --> 02:12:02.280
how the State library administrative
agencies are contributing to make

1407
02:12:02.280 --> 02:12:07.520
healthy libraries and we used to use the
metaphor of can we better describe the

1408
02:12:07.520 --> 02:12:11.760
way a summer investment in a summer
reading program and say Michigan differs

1409
02:12:11.760 --> 02:12:16.639
from Mississippi or looks the same and
back then the way the reports used to do

1410
02:12:16.639 --> 02:12:22.440
for your lsta grants you had probably
about 3,000 projects we be getting

1411
02:12:22.440 --> 02:12:27.880
nationally and they were all basically a
lot of words and stories it made it

1412
02:12:27.880 --> 02:12:33.719
really hard to tell National story so
the whole spr

1413
02:12:33.719 --> 02:12:40.679
dense um comprehensive but it's also
structured so that we can tell stories

1414
02:12:40.679 --> 02:12:45.159
about where the dollars go and what it
looks like for State libraries and the

1415
02:12:45.159 --> 02:12:52.000
other libraries within those States and
territories and so we built it out over

1416
02:12:52.000 --> 02:12:55.639
four years and it was this Federal
partnership that we had like 15 states

1417
02:12:55.639 --> 02:13:02.320
who were partnering us piloting coaching
others and we kind of kept building on

1418
02:13:02.320 --> 02:13:09.239
it and um it's kind of the big picture
we want to talk a little bit today about

1419
02:13:09.239 --> 02:13:13.920
that big picture and about what we might
want to be looking at different talk a

1420
02:13:13.920 --> 02:13:16.920
little bit about some of the things and
also some of the things that happened

1421
02:13:16.920 --> 02:13:23.559
compared to last year and I'm also one
who spent a lot of time in Wisconsin and

1422
02:13:23.559 --> 02:13:30.360
at 4:05 p.m. I used to teach in Madison
and ashkash and I has a you know great

1423
02:13:30.360 --> 02:13:35.040
fascinating classes on statistics and
experimental designs so we used to run

1424
02:13:35.040 --> 02:13:40.079
the hypothesis of what would put you to
sleep more effectively at this time of

1425
02:13:40.079 --> 02:13:46.119
day ambien or me so you know that's
going to be the big pictures but on the

1426
02:13:46.119 --> 02:13:51.199
bottom right we've got Leon's custard
about four miles from here also in Ash

1427
02:13:51.199 --> 02:13:58.599
gosh where I went went mly two two times
the far left is that uh tesen yeah so

1428
02:13:58.599 --> 02:14:02.199
that's you know you can go about two
hours to the west and the Southwest that

1429
02:14:02.199 --> 02:14:06.320
hour west of Madison right in the
prairie is where Frank Lloyd Wright uh

1430
02:14:06.320 --> 02:14:10.320
had his first architectural school and
um you know one of the great

1431
02:14:10.320 --> 02:14:15.280
architectural planning Giants of the
world and in the center we're looking at

1432
02:14:15.280 --> 02:14:20.480
about 45 minutes to the northwest of
here an area called Huracan Marsh which

1433
02:14:20.480 --> 02:14:25.400
for those of you who um like cranes and
other amazing birds in this really

1434
02:14:25.400 --> 02:14:29.920
fascinating migration path card or here
the Huracan Marsh is just an a amazing

1435
02:14:29.920 --> 02:14:34.639
Place particularly this time of
year so back to you

1436
02:14:34.639 --> 02:14:39.520
Terry I'm gonna I'm gonna give you the
lightning round of my slides so this is

1437
02:14:39.520 --> 02:14:45.520
what Matt was describing also um tell us
about this slide this picture slide yeah

1438
02:14:45.520 --> 02:14:51.119
yeah so about 2 hours north of here in
Hayward Wisconsin there is a intern

1439
02:14:51.119 --> 02:14:55.119
ational race of cross country skiers
every year it's sow permitting called

1440
02:14:55.119 --> 02:15:00.199
the uh burken and the burken has got
literally tens of thousands of people

1441
02:15:00.199 --> 02:15:04.960
from the most elite races who we see in
the Olympics to just people everyday

1442
02:15:04.960 --> 02:15:08.880
people who really going to make the
adventure like doing a marathon or a

1443
02:15:08.880 --> 02:15:14.239
century bike ride this is kind of one of
the rituals for Wisconsin Winters is the

1444
02:15:14.239 --> 02:15:19.800
burken nice so yeah last year we had a
long conversation with you we talked

1445
02:15:19.800 --> 02:15:23.480
about these principles for engagement
which you've seen a little bit on

1446
02:15:23.480 --> 02:15:28.520
Clifton's
slides uh we heard a lot of what you had

1447
02:15:28.520 --> 02:15:33.840
in terms of feedback last year and we
have started to implement some

1448
02:15:33.840 --> 02:15:38.679
enhancements in the system um I want to
thank all the states that have been

1449
02:15:38.679 --> 02:15:43.320
giving us feedback um and tell you that
we're still working on the Preparatory

1450
02:15:43.320 --> 02:15:47.559
work for the multiactor authentication
which is going to be

1451
02:15:47.559 --> 02:15:51.559
login.gov but the real story and so
these are just

1452
02:15:51.559 --> 02:15:56.159
um yes also Wisconsin related things
Madison Bulls is actually drinking a

1453
02:15:56.159 --> 02:16:00.400
sper rot beer as we speak and if you'd
like to visit dor County or Wisconsin

1454
02:16:00.400 --> 02:16:05.480
Dells I'm sure our Chamber of Commerce
could tell you all about it here but for

1455
02:16:05.480 --> 02:16:09.920
the big picture of what's been happening
since last year it's really we're

1456
02:16:09.920 --> 02:16:15.119
getting the system back to good we got a
new developer who is very very competent

1457
02:16:15.119 --> 02:16:18.639
and after he started looking under the
hood there was a lot of stuff that

1458
02:16:18.639 --> 02:16:22.800
needed fixing you have also helped us
identify a lot of stuff that needed

1459
02:16:22.800 --> 02:16:27.440
fixing so For Better or For Worse that's
where last year's energies were going we

1460
02:16:27.440 --> 02:16:32.880
still have all of your feedback logged
we're hoping to make more progress on it

1461
02:16:32.880 --> 02:16:37.200
um and we thank you thank you thank you
for your patience in working with us on

1462
02:16:37.200 --> 02:16:43.200
all of these little fixes and
bugs um some of the new spr enhancements

1463
02:16:43.200 --> 02:16:48.880
that we are thinking about just preview
of hopes and dreams we do know that the

1464
02:16:48.880 --> 02:16:55.719
beneficiary age ranges in our spr don't
align perfectly with PLS data or the SLA

1465
02:16:55.719 --> 02:17:00.399
survey data and we want to align those
eventually we do want to lock down the

1466
02:17:00.399 --> 02:17:04.880
Dual user thing in other parts of the
spr where data loss could happen like

1467
02:17:04.880 --> 02:17:10.920
the site visit checklist we want to
potentially Implement data validation at

1468
02:17:10.920 --> 02:17:17.760
a more discret um level in The
spr increased file size and possible

1469
02:17:17.760 --> 02:17:22.679
public view inclusion of additional
materials so coming soon soon and then

1470
02:17:22.679 --> 02:17:26.519
we login.gov has not been forgotten it's
just we had to back burner it for all

1471
02:17:26.519 --> 02:17:31.399
that other stuff on the slide so we're
going to start to message you when this

1472
02:17:31.399 --> 02:17:35.080
is coming and we're going to do it in
phases so it's not going to be like a

1473
02:17:35.080 --> 02:17:39.639
switch flipping overnight we're going to
give you a warning like it's coming here

1474
02:17:39.639 --> 02:17:44.559
you can preview it in our test system
okay guys it's coming but you still got

1475
02:17:44.559 --> 02:17:49.280
a little grace period if you still want
to use your passwords and then phase

1476
02:17:49.280 --> 02:17:54.319
three the switch is is flipping and so
if you have subrecipients that are

1477
02:17:54.319 --> 02:17:59.120
actively engaging in the spr we want you
to at that point you know start

1478
02:17:59.120 --> 02:18:03.359
messaging with them as well so we're
going to send you more stuff on this

1479
02:18:03.359 --> 02:18:08.160
that is the coming soon but the real
this is like the treat at the end of the

1480
02:18:08.160 --> 02:18:12.359
day Matt has the treat slide yeah so
we're back on Frozen Custard which is

1481
02:18:12.359 --> 02:18:17.000
going to be a theme for the day then we
got some fried cheese curds um to the

1482
02:18:17.000 --> 02:18:22.639
right okay if you go back 10 years in
time with just rolling out the spr we're

1483
02:18:22.639 --> 02:18:26.960
in this type of meeting we're doing all
the training get everybody ready to do

1484
02:18:26.960 --> 02:18:33.280
it we were also getting ready to start
launching uh the last part of the which

1485
02:18:33.280 --> 02:18:37.840
was surveying of
beneficiaries and we knew we weren't

1486
02:18:37.840 --> 02:18:42.880
going to require it for every project if
you were procuring a piece there really

1487
02:18:42.880 --> 02:18:48.439
wasn't much sense of going ahead and
surveying somebody but if by contrast

1488
02:18:48.439 --> 02:18:54.160
she were doing some programming of maybe
a certain target audience maybe it

1489
02:18:54.160 --> 02:18:58.639
really would make sense to see how was
that touching that audience and that

1490
02:18:58.639 --> 02:19:04.800
idea made a lot of not specific to
Grants to States for libraries did it

1491
02:19:04.800 --> 02:19:10.800
make sense for this particular program
but it reflected about 40 Years of

1492
02:19:10.800 --> 02:19:16.920
interest in public and philanthropic
Investments people taxpayers or

1493
02:19:16.920 --> 02:19:20.519
philanthropists who are paying for these
Services they want to know what's the

1494
02:19:20.519 --> 02:19:24.280
return Returns on
investment so we're going to be spending

1495
02:19:24.280 --> 02:19:28.880
this types of hundreds of millions of
dollars for libraries using Federal

1496
02:19:28.880 --> 02:19:35.559
taxpayer dollars what's the outcome so
the intent here was where it made sense

1497
02:19:35.559 --> 02:19:40.639
could we start to survey beneficiaries
and we knew it was happening outside the

1498
02:19:40.639 --> 02:19:46.800
library sector we also knew outside of
imls that the Public Library Association

1499
02:19:46.800 --> 02:19:51.560
was working with a number of libraries
to start doing the same thing 10 years

1500
02:19:51.560 --> 02:19:56.000
ago Emily she didn't show us the photo
today but she was wearing that hat in

1501
02:19:56.000 --> 02:20:00.600
terms of developing project outcome for
Public Library Association so when we

1502
02:20:00.600 --> 02:20:04.600
were in this conversation 10 years ago
it wasn't so much should we do this

1503
02:20:04.600 --> 02:20:10.120
surveying but how can we do in a way
that really limits the burden for those

1504
02:20:10.120 --> 02:20:14.880
public libraries who were getting the
formula grant dollars from the SLA

1505
02:20:14.880 --> 02:20:20.000
through imls and also participating in
Project outcomes so we aligned it so

1506
02:20:20.000 --> 02:20:25.080
people weren't having to do two separate
surveys be the same type of

1507
02:20:25.080 --> 02:20:31.600
survey that being said the best
Ambitions the best hopes don't always go

1508
02:20:31.600 --> 02:20:37.920
as intended and we know that there's
been real mixed success and we don't

1509
02:20:37.920 --> 02:20:42.720
really really haven't studied it yet but
you know I've got a hypothesis out there

1510
02:20:42.720 --> 02:20:46.960
that says that the way the surveying is
going even when it's done right it may

1511
02:20:46.960 --> 02:20:51.560
not be as utilized the way we initially
had aspired

1512
02:20:51.560 --> 02:20:56.040
but before we throw the baby out with
the bath water we

1513
02:20:56.040 --> 02:21:04.200
might the
um sorry Emily no no no no offense that

1514
02:21:04.200 --> 02:21:09.960
um we really want to make and ask for
you everything we do is federal state

1515
02:21:09.960 --> 02:21:15.040
partnership we'd like to put to use this
year and come back next year to do some

1516
02:21:15.040 --> 02:21:20.120
homework to really start looking at what
are the types of outcomes that we can be

1517
02:21:20.120 --> 02:21:23.720
assessing
how effective and useful is that

1518
02:21:23.720 --> 02:21:28.680
evidence for you and other key
audiences and what would it look like if

1519
02:21:28.680 --> 02:21:34.200
we suddenly stop doing the surveying to
reduce that burden what would be some of

1520
02:21:34.200 --> 02:21:39.319
the costs or benefits of trying to do
either nothing or something

1521
02:21:39.319 --> 02:21:45.359
else so I want to stop there and Terry
do you want to add anything to

1522
02:21:45.359 --> 02:21:49.720
this just in case you're wondering what
those outcome surveys are it's the

1523
02:21:49.720 --> 02:21:52.880
questions like
I learned something by using this

1524
02:21:52.880 --> 02:21:56.840
Library resource I plan to use more
Library resources because I'm using this

1525
02:21:56.840 --> 02:22:01.080
resource and so they're like formulated
questions that we have given you to

1526
02:22:01.080 --> 02:22:05.359
deliver to some of your end users who go
to programs and we know they're very

1527
02:22:05.359 --> 02:22:10.439
hard for you to collect and and give
back to us and enter in the spr so that

1528
02:22:10.439 --> 02:22:15.640
that is all what we are talking about
here like what is the ROI on that and

1529
02:22:15.640 --> 02:22:22.200
we're going to investigate that the
Smart Ones at that table yeah okay I

1530
02:22:22.200 --> 02:22:27.240
think we did yeah any questions or
comments about

1531
02:22:27.600 --> 02:22:32.800
this you know we're keeping them from we
know the ambient is really kward no no

1532
02:22:32.800 --> 02:22:38.280
but we've got exciting things to come so
don't fall asleep on us yet not

1533
02:22:38.280 --> 02:22:42.560
yet okay thank you hey Terry thank you
for giving our thank you everybody for

1534
02:22:42.560 --> 02:22:46.200
giving our my team here a chance to par

1535
02:22:46.560 --> 02:22:52.359
participate thank
you officer of research and

1536
02:22:52.359 --> 02:22:59.080
evaluation we are transitioning into the
funnest happiest time of the day the

1537
02:22:59.080 --> 02:23:05.120
kind of madeup awards that we create
each year they they have no basis in in

1538
02:23:05.120 --> 02:23:10.439
things except what we really care about
as your program officer staff at imls um

1539
02:23:10.439 --> 02:23:16.120
so I'm going to bring up Laura McKenzie
who's GNA sort of read you this part of

1540
02:23:16.120 --> 02:23:20.600
the program and then our program
officers are going to give you your

1541
02:23:20.600 --> 02:23:26.760
Awards should you choose to accept them
and um we'll get it in a minute I'm

1542
02:23:26.760 --> 02:23:30.040
going to stay right here and just
continue to introduce Laura she's our

1543
02:23:30.040 --> 02:23:34.960
program specialist for the program she
is the glue the bridge that holds us

1544
02:23:34.960 --> 02:23:40.000
together she's helped project manage us
through all the conference planning

1545
02:23:40.000 --> 02:23:45.160
she's been nobly working the virtual
channels all day and this is the one

1546
02:23:45.160 --> 02:23:50.520
chance we get to really hear from her um
she actually stepped up and created the

1547
02:23:50.520 --> 02:23:56.920
cute award categories that you're going
to see in the next section and um so I'm

1548
02:23:56.920 --> 02:24:03.279
just so thrilled to welcome up Laura and
the program officers and I will get the

1549
02:24:03.279 --> 02:24:06.640
the awards props one

1550
02:24:06.650 --> 02:24:11.879
[Applause]

1551
02:24:14.680 --> 02:24:20.640
moment just want to say it's a cheese
platter

1552
02:24:29.120 --> 02:24:33.880
all right
well uh before I kick off the official

1553
02:24:33.880 --> 02:24:38.520
Awards portion I just wanted to uh
remind everybody that we have our office

1554
02:24:38.520 --> 02:24:46.600
hours uh here in this room uh after this
session and if you had any parking lot

1555
02:24:46.600 --> 02:24:52.120
questions uh please feel free to put
them on the easel

1556
02:24:52.120 --> 02:24:56.160
and don't forget the peer-to-peer
appreciation wall uh which we'll also

1557
02:24:56.160 --> 02:25:01.760
revisit
tomorrow and now for the fun

1558
02:25:01.760 --> 02:25:06.960
part so every year we really look
forward to celebrating all of you here

1559
02:25:06.960 --> 02:25:11.560
based on different
achievements and we know that several of

1560
02:25:11.560 --> 02:25:17.319
our recipients are joining us virtually
uh so we will recognize you as well uh

1561
02:25:17.319 --> 02:25:20.880
you won't be able to come up and get a
picture and a certificate

1562
02:25:20.880 --> 02:25:25.520
but I will email you your certificate
after the

1563
02:25:25.520 --> 02:25:30.160
conference and so we have some
certificates cheese stress balls for

1564
02:25:30.160 --> 02:25:34.920
each uh
awarde and we'd love uh if you're here

1565
02:25:34.920 --> 02:25:40.319
in person if you stayed at the front of
the room for a

1566
02:25:40.399 --> 02:25:47.600
picture and in keeping with our
Wisconsin theme we will kick it off with

1567
02:25:47.600 --> 02:25:52.279
the sharp Cheddars award
this

1568
02:25:52.279 --> 02:26:01.359
recognizes uh those who did their
earliest uh FY 2023 interum ffr

1569
02:26:01.359 --> 02:26:08.520
submission and we'll start with uh
Madison's portfolio uh North

1570
02:26:13.479 --> 02:26:19.279
Carolina and Cindy uh Utah

1571
02:26:29.840 --> 02:26:37.000
and Dennis we have New Mexico and I know
that they are joining us virtually so

1572
02:26:37.000 --> 02:26:40.219
[Applause]

1573
02:26:41.439 --> 02:26:47.520
congratulations uh next up is the Ina
compliance award for same day

1574
02:26:47.520 --> 02:26:51.520
certification submission

1575
02:26:52.080 --> 02:26:58.240
and again uh we'll start with Madison's
uh portfolio we have

1576
02:26:58.240 --> 02:27:01.240
maryn

1577
02:27:01.820 --> 02:27:04.950
[Applause]

1578
02:27:10.399 --> 02:27:18.680
uh and Maine I know they are also
joining us virtually congratulations

1579
02:27:20.520 --> 02:27:28.359
uh Michigan and we have a couple
inperson and Michelle Bradley's

1580
02:27:42.240 --> 02:27:46.560
virtual and Ohio

1581
02:27:57.200 --> 02:28:00.360
and Puerto
[Laughter]

1582
02:28:00.360 --> 02:28:06.009
[Applause]

1583
02:28:12.960 --> 02:28:15.960
Rico

1584
02:28:18.120 --> 02:28:23.720
congratulations all right
next up uh

1585
02:28:33.960 --> 02:28:36.960
Massachusetts

1586
02:28:37.580 --> 02:28:41.950
[Applause]

1587
02:28:44.760 --> 02:28:51.520
Oklahoma and Utah yes Utah again

1588
02:28:58.359 --> 02:29:03.760
all
right and now for Dennis's portfolio uh

1589
02:29:03.760 --> 02:29:08.359
Alabama this was before the award was
even issued this was

1590
02:29:08.359 --> 02:29:13.520
remarkable thank you then they are
joining us virtually so

1591
02:29:13.520 --> 02:29:18.240
congratulations and we also have
Pennsylvania

1592
02:29:31.080 --> 02:29:39.799
and New York
[Applause]

1593
02:30:08.120 --> 02:30:14.560
right all right this is our largest
category uh which

1594
02:30:14.560 --> 02:30:21.479
is the greatest Spenders
award acknowledge ing arpa spending down

1595
02:30:21.479 --> 02:30:27.240
to the
penny kick it off with

1596
02:30:29.640 --> 02:30:34.270
[Applause]

1597
02:30:39.240 --> 02:30:43.600
Connecticut and DC

1598
02:30:45.170 --> 02:30:48.309
[Applause]

1599
02:30:55.880 --> 02:31:01.310
[Applause]

1600
02:31:03.880 --> 02:31:10.399
Hawaii
Maine uh virtually yes uh

1601
02:31:10.610 --> 02:31:13.780
[Applause]

1602
02:31:17.160 --> 02:31:21.160
Maryland Michigan

1603
02:31:31.640 --> 02:31:34.120
North

1604
02:31:34.570 --> 02:31:41.009
[Applause]

1605
02:31:47.120 --> 02:31:53.970
Carolina Ohio
[Laughter]

1606
02:32:03.080 --> 02:32:05.920
and Rhode

1607
02:32:06.230 --> 02:32:12.969
[Applause]

1608
02:32:13.920 --> 02:32:18.640
Island
yes all right now we have Colorado who

1609
02:32:18.640 --> 02:32:23.520
is with us virtually
Georgia who is also with us

1610
02:32:23.520 --> 02:32:34.929
virtually uh Kansas
[Applause]

1611
02:32:53.120 --> 02:32:55.960
thank you

1612
02:33:06.319 --> 02:33:09.319
Kentucky

1613
02:33:09.600 --> 02:33:13.600
that's Massachusetts

1614
02:33:14.010 --> 02:33:19.090
[Applause]

1615
02:33:20.200 --> 02:33:26.720
uh Nebraska who is online
congratulations

1616
02:33:32.200 --> 02:33:35.370
[Laughter]

1617
02:33:36.240 --> 02:33:41.080
Nevada and Oregon also with us

1618
02:33:41.439 --> 02:33:45.880
online South Carolina

1619
02:33:46.060 --> 02:33:52.230
[Applause]

1620
02:33:59.040 --> 02:34:02.680
Utah again

1621
02:34:03.990 --> 02:34:07.649
[Applause]

1622
02:34:08.319 --> 02:34:12.319
yes Vermont

1623
02:34:13.050 --> 02:34:17.899
[Applause]

1624
02:34:25.990 --> 02:34:33.080
[Applause]
Washington and

1625
02:34:33.470 --> 02:34:40.830
[Applause]

1626
02:34:44.520 --> 02:34:52.000
Wyoming all right and Alabama hello
virtually congrat conratulations

1627
02:34:54.750 --> 02:34:58.440
[Applause]

1628
02:35:03.359 --> 02:35:06.359
Arkansas

1629
02:35:11.920 --> 02:35:15.920
Indiana Iowa

1630
02:35:16.230 --> 02:35:19.540
[Applause]

1631
02:35:23.520 --> 02:35:28.279
Louisiana also virtual uh

1632
02:35:29.810 --> 02:35:34.969
[Applause]

1633
02:35:37.479 --> 02:35:40.840
Mississippi and

1634
02:35:44.790 --> 02:35:50.160
[Applause]
Montana and New Mexico

1635
02:35:50.160 --> 02:35:54.720
congratulations online uh New

1636
02:35:55.210 --> 02:36:00.879
[Applause]

1637
02:36:07.319 --> 02:36:12.760
York and Pennsylvania

1638
02:36:13.770 --> 02:36:20.219
[Applause]

1639
02:36:25.600 --> 02:36:30.600
Tennessee their virtual uh West

1640
02:36:32.780 --> 02:36:40.520
[Applause]
Virginia and Wisconsin

1641
02:36:40.520 --> 02:36:48.480
[Applause]

1642
02:37:08.680 --> 02:37:12.759
[Applause]

1643
02:37:13.080 --> 02:37:16.080
you

1644
02:37:20.040 --> 02:37:27.960
all right our next category is the big
cheese People's Choice Awards um this is

1645
02:37:27.960 --> 02:37:36.880
from the registration form uh some of
you uh submitted some uh award here uh

1646
02:37:36.880 --> 02:37:40.520
starting with Karen reach of

1647
02:37:44.160 --> 02:37:49.880
Michigan
um she was nominated by Dina ratl Warren

1648
02:37:49.880 --> 02:37:54.120
uh who said always willing to help
answer questions and share her time and

1649
02:37:54.120 --> 02:37:59.279
talents she was also nominated by Mora
Walsh and Erica

1650
02:37:59.279 --> 02:38:04.720
McCormack Erica said Karen always
contributes a response to the list serve

1651
02:38:04.720 --> 02:38:11.560
and has good suggestions I keep my lstc
lsac messages to go back and see what

1652
02:38:11.560 --> 02:38:16.930
she says about a certain
topic congratulations

1653
02:38:16.930 --> 02:38:20.149
[Applause]

1654
02:38:20.840 --> 02:38:25.479
and next we have sulin Jones of

1655
02:38:29.399 --> 02:38:35.600
Nevada she was nominated by Mora Walsh
and Erica McCormack uh Erica said that

1656
02:38:35.600 --> 02:38:40.560
suin Jones is always a wealth of
information uh in Zoom calls and in

1657
02:38:40.560 --> 02:38:45.520
person she is eager to share her
knowledge and experiences and she was

1658
02:38:45.520 --> 02:38:50.840
also nominated by Claire imamura who
said I appreciate suin Jones sense of

1659
02:38:50.840 --> 02:38:57.920
humor and cander she was a great help to
me when I was new to the lsta and a fun

1660
02:38:57.920 --> 02:39:03.040
grants to State's
buddy

1661
02:39:06.520 --> 02:39:12.950
congratulations and Mara Walsh of New
Jersey is also

1662
02:39:12.950 --> 02:39:16.359
[Applause]

1663
02:39:16.680 --> 02:39:22.000
nominated she was nominated by Erica
cormi who said that Mora always

1664
02:39:22.000 --> 02:39:28.160
contributes a response to the list serve
and has good suggestions I keep my LST

1665
02:39:28.160 --> 02:39:33.520
AC messages to go back and see what she
says about a certain

1666
02:39:33.520 --> 02:39:38.200
topic
[Applause]

1667
02:39:38.200 --> 02:39:42.800
congratulations and I also wanted to
recognize a couple of nominees who are

1668
02:39:42.800 --> 02:39:50.680
not here in person uh but Terry Taylor
was nominated uh by you La wsh we do

1669
02:39:50.680 --> 02:39:54.479
have a certificate for you to take home
uh to

1670
02:39:54.479 --> 02:40:01.680
her and Michelle Killian uh formerly of
California was nominated by Amanda gamon

1671
02:40:01.680 --> 02:40:06.439
uh who said she helped support the lsta
program team daily is always thinking

1672
02:40:06.439 --> 02:40:12.359
about how to best help lsta awardees and
is a great advocate for California's

1673
02:40:12.359 --> 02:40:17.640
libraries and we have a certificate
Amanda that you can take home to

1674
02:40:17.640 --> 02:40:23.880
Michelle and then Rachel cook uh
formerly of Utah um she was nominated by

1675
02:40:23.880 --> 02:40:29.800
Shannon furo of of Georgia who said I
know she's not an lsta coordinator

1676
02:40:29.800 --> 02:40:35.520
anymore but she was super helpful to me
this last year we need to overhaul and

1677
02:40:35.520 --> 02:40:41.600
update our subgrant process she took
time out to show me a demo of how her

1678
02:40:41.600 --> 02:40:46.160
grants management system works shared
templates and it was available for my

1679
02:40:46.160 --> 02:40:50.600
numerous
questions so congrat congratulation to

1680
02:40:50.600 --> 02:40:53.240
all the

1681
02:40:54.090 --> 02:41:00.930
[Applause]

1682
02:41:07.080 --> 02:41:13.359
recipients and last but certainly not
least we wanted to recognize all of

1683
02:41:13.359 --> 02:41:19.600
you I mean there are so many things here
to recognize uh for example a full WP up

1684
02:41:19.600 --> 02:41:26.560
of arpa including cares and arpa
interviews spr goal updates close out of

1685
02:41:26.560 --> 02:41:32.920
the 2018 to 2022 cycle uh we also
appreciate how many of you shared press

1686
02:41:32.920 --> 02:41:37.800
releases and news about your
projects and there were so many strong

1687
02:41:37.800 --> 02:41:48.240
site visits this year Arkansas Colorado
Delaware Iowa Hawaii Kansas Maine

1688
02:41:48.240 --> 02:41:54.920
Mississippi Montana Nevada North
Carolina South Carolina and

1689
02:41:54.920 --> 02:42:01.680
Wisconsin and that formally concludes
our recognition event