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Record W4388115096 · doi:10.18438/b8863

Small Library Research: Using Qualitative and User-Oriented Research to Transform a Traditional Library into an Information Commons

2017· article· en· W4388115096 on OpenAlexvenueno aff
Quincy Dalton McCrary

Bibliographic record

VenueEvidence Based Library and Information Practice · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Administration
Canadian institutionsnot available
Fundersnot available
KeywordsComputer scienceSpace (punctuation)World Wide WebMeaning (existential)CommonsLibrary instructionInformation literacyValue (mathematics)Library sciencePsychologyPolitical science

Abstract

fetched live from OpenAlex

Abstract
 
 Objective - The project team investigated the changes necessary to transform the original library into an information commons. The researchers sought to drive the project by asking for patrons’ input, rather than rely on the vision of administrators or librarians.
 
 Methods - The project team used four techniques to gather data. They recorded patron use patterns, administered surveys, conducted formal interviews, and facilitated comment boards. 
 
 Results - Each of the four methods used in this research delivered similar conclusions. Patrons used the library as a study hall, but the space did not facilitate collaboration. Patrons requested more group study spaces, more access to power, and a quieter environment. Patrons identified the value of developing a learning community in the library. Finally, patrons advocated for the retention of physical collections in the library building. 
 
 Conclusion - The present library building, designed to facilitate individual, quiet, textual based learning, no longer serves the needs of its patrons. Analysis of this project’s data supports the need to develop an information commons. The Gellert Library is not just a place to store books and study. Rather, it is a place where meaning and learning emerges from access to knowledge.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesScholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.888
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.001
Scholarly communication0.0080.717
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.355
GPT teacher head0.476
Teacher spread0.120 · 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; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
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".

Quick stats

Citations1
Published2017
Admission routes1
Has abstractyes

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