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Record W2809523343 · doi:10.1017/alj.2018.19

Bookworms as information literacy? How Henri Lefebvre's spatial triad encouraged OCAD University to re-place the art library through site-interventions

2018· article· en· W2809523343 on OpenAlexaff
Daniel Payne

Bibliographic record

VenueArt Libraries Journal · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Administration
Canadian institutionsOntario College of Art and Design
Fundersnot available
KeywordsExhibitionTriad (sociology)Information literacyVisual literacyPsychological interventionPerceptionSociologyLiteracyLibrary scienceVisual artsPublic relationsPedagogyPsychologyPolitical scienceComputer scienceArtSocial science

Abstract

fetched live from OpenAlex

Does the art library need re-placing? Using the commentary of an OCAD University faculty member concerning “a perception issue with the library and its use,” librarian Daniel Payne uses theorist Henri Lefebvre's spatial triad to decode, in general terms, undergraduate students’ understanding of libraries as articulated in the OCLC Perceptions of libraries surveys. In an attempt to re-align concepts of the library as place at OCAD University, an exhibition review interpretation of student site-interventions demonstrates how visual communication can offer more insightful “spatial practices” for both students and library staff. In the process, librarians were challenged to accommodate student creative voices that pushed both policy boundaries and comfort zones. Although a small-scale information literacy initiative in which no formal quantitative data was collected, the ability of having conceptual models of librarians interact and even clash with those of students helped realign both stakeholders’ understandings of libraries as complex spatial entities.

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)0.006
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.986
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.017
Scholarly communication0.0140.012
Open science0.0010.005
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0090.001

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 head0.026
GPT teacher head0.286
Teacher spread0.260 · 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.

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".

Quick stats

Citations3
Published2018
Admission routes1
Has abstractyes

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