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Record W3097140745 · doi:10.5206/elip.v3i1.8624

How Libraries Make us Believe

2020· article· en· W3097140745 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueEmerging Library & Information Perspectives · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Administration
Canadian institutionsWestern University
Fundersnot available
KeywordsObfuscationOrder (exchange)Computer scienceAcademic librarySociologyData scienceEpistemologyLibrary scienceBusinessComputer security

Abstract

fetched live from OpenAlex

This paper considers how the physical spaces of academic libraries actively assert the belief of intellectual pursuit upon users. Taking up Thomas Gieryn’s concept of “truth-spots,” this paper argues that the academic library is particularly effective at encapsulating and expressing this pursuit through its own spatial configurations. Library spaces achieve this through the manipulation of time, spatial gathering and separation, an imposed order, exposure and obfuscation, as well as the library’s unique or standardized configurations. This paper invites us to think about the library’s metaphysicality in terms that connect abstract beliefs to the library’s physical materials and spaces. The purpose of this paper is to identify the subtle, yet powerful, spatial changes occurring in recent efforts to reconfigure academic library spaces. The implications of such a consideration may aid to inform future (re)designs of library spaces.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesScholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.899
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0020.045
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.248
Teacher spread0.229 · 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