The Public Library Catalogue as a Social Space: A Case Study of Social Discovery Systems in Two Canadian Public Libraries
Bibliographic record
Abstract
This paper uses transaction log data to examine how library users interact with two social discovery systems used in two Canadian public library systems. Results indicate that user-generated content is not used extensively or significantly in the two social discovery systems. Format is the predominant facet used to refine searches; the remaining facets are significantly underrepresented.Cette étude utilise les journaux transactionnels pour déterminer comment les usagers des bibliothèques interagissent avec deux systèmes de découverte sociaux en place dans deux réseaux de bibliothèques publiques canadiennes. Les résultats indiquent que le contenu généré par les utilisateurs n’est pas utilisé à grande échelle ou de façon importante dans aucun des deux systèmes de découverte sociaux. Le format est la principale facette utilisée pour raffiner les recherches; les autres facettes étant sous-représentées.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.018 |
| Science and technology studies | 0.016 | 0.006 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".