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Record W2204557665 · doi:10.18438/b8602c

Thematic Analysis of Videos Suggests That YA Space Design Should Be User-Driven, User-Centered, and Flexible Enough to Enable Multiple Uses

2015· article· en· W2204557665 on OpenAlexvenueno aff
Ann Glusker

Bibliographic record

VenueEvidence Based Library and Information Practice · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Administration
Canadian institutionsnot available
Fundersnot available
KeywordsUSableThematic analysisSpace (punctuation)NarrativeLibrary scienceTheme (computing)Computer scienceThematic mapWorld Wide WebPublic spaceSociologyQualitative researchArtEngineeringSocial scienceLiteratureCartographyGeography

Abstract

fetched live from OpenAlex

A Review of: Agosto, D. E., Bell, J. P., Bernier, A. & Kuhlmann, M. (2015). “This is our library, and it’s a pretty cool place”: A user-centered study of public library YA spaces. Public Library Quarterly, 34(1), 23-43. doi: http://dx.doi.org/10.1080/01616846.2015.1000777 Objective – To add empirical evidence to the study of young adult (YA) spaces and creation of related guidelines by investigating librarians’ and teens’ perceptions of YA spaces and their use in public libraries. Design – Qualitative thematic analysis of video data content. Setting – 25 public libraries in the United States of America. Subjects – A librarian, and a teen of their choosing, at each of the 25 selected libraries. Methods – The researchers chose 25 public libraries randomly from a list of 257 libraries profiled from 2005-2010 in Library Journal’s annual index of new and renovated libraries. Each of the 25 libraries was sent a video camera, and the selected librarian and teen each recorded a narrated tour of their library’s YA space. The cameras were returned to the researchers, who had the audio of the recordings transcribed, referring back to the video for any narration that needed clarification. Thematic analysis was performed on the transcriptions to identify major- and sub-categories of space and space-use characteristics. Empirical results were reported as a numerical figure representing the number of videos (n=42 total usable videos) in which a particular theme was mentioned at least once. Main Results – Five main categories of YA space characteristics recommended by teens and librarians emerged from the thematic analysis. YA spaces need to facilitate: physical comfort; both leisure activity and information needs; both academic activity and information needs; a sense of ownership by teens; and improved marketing of the spaces as well as clear displays of library policies regarding the spaces. Sub-categories were also listed in each instance, as were counts and percentages of numbers of videos in which a theme was mentioned at least once. Conclusion – YA spaces in public libraries need to be user-centered, and the arrangements need to be flexible enough to be used for multiple purposes. Teens need to be involved in and drivers of their design and ongoing use. In addition, teens’ needs for social interaction, and leisure as well as academic support, must be explicitly incorporated into any planning. Librarians and libraries must adjust their focus on resources to better mirror teens’ focus on the activities that happen in YA spaces, both online and in person. In order to serve YA patrons, libraries must also actively promote YA spaces. This initial exploratory empirical investigation can inform future much-needed research on improving YA space planning. Research is also needed to examine the evolution of libraries’ YA investments as teen patrons’ needs change over time.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.019
metaresearch head score (Gemma)0.033
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.103

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.033
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0040.006
Scholarly communication0.0040.009
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.139
GPT teacher head0.346
Teacher spread0.207 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2015
Admission routes1
Has abstractyes

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