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Record W2621215181 · doi:10.29173/cais865

OPACs, Users, and Readers’ Advisory: Exploring the Implication of User-Generated Content for Readers’ Advisory in Canadian Public Libraries

2016· article· fr· W2621215181 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.

venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueProceedings of the Annual Conference of CAIS / Actes du congrès annuel de l ACSI · 2016
Typearticle
Languagefr
FieldComputer Science
TopicWeb and Library Services
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceLibrary scienceHumanitiesArtComputer science

Abstract

fetched live from OpenAlex

An analysis of user-generated content (UGC) of 22 adult fiction titles in 43 Canadian public libraries that use BiblioCommons, SirsiDynix, and Encore was conducted to examine the contribution of UGC on readers’ advisory services. Findings indicate that UGC provides insight into the affect, subject, and protagonists of a work.Nous avons procédé à une analyse de contenus générés par les utilisateurs sur 22 titres de fiction pour adultes dans 43 bibliothèques publiques canadiennes utilisant BiblioCommons, SirsiDynix et Encore, afin d’examiner la contribution du contenu généré par les utilisateurs aux services d’avis aux lecteurs. Les résultats indiquent que les contenus générés par les utilisateurs donnent un aperçu sur le sujet, les protagonistes et les affects d'une oeuvre.

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)0.001
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesScholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.485
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0030.033
Open science0.0030.001
Research integrity0.0000.000
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 head0.099
GPT teacher head0.243
Teacher spread0.144 · 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