L’état des frontières sous-disciplinaires en bibliothéconomie et sciences de l’information
Bibliographic record
Abstract
Cette présentation d’une thèse de doctorat en cours explore la structure disciplinaire de la bibliothéconomie et des sciences de l’information (BSI) en analysant 206 thèses canadiennes complétées entre 2010 et 2024. L’étude examine la répartition des recherches par sous-champs, l’influence des disciplines externes, le corpus de littérature commun et les choix épistémiques des thèses. À travers des analyses bibliométriques et qualitatives, elle vise à mieux comprendre la fragmentation de la discipline et les interactions interdisciplinaires, tout en mettant en lumière les implications pour la cohésion et le développement de la BSI. Des résultats préliminaires seront disponibles pour la conférence. The State of Sub-Disciplinary Borders in Library and Information Science : Between Porosity and Impermeabiliy AbstractThis presentation of a doctoral thesis in progress explores the disciplinary structure of library and Information science (LIS) by analyzing 206 Canadian theses completed between 2010 and 2024. The study looks at the distribution of research by sub-categories, the impact of external disciplines, the common literary corpus and the theses’ epistemic choices. Through bibliometric and qualitative analyses, the study aims to better comprehend the fragmentation of the discipline and the interdisciplinary interactions, while highlighting the implications for the cohesion and development of LIS. Preliminary results will be available at the conference. KeywordsLibrary and information science; disciplines; Disciplinary borders; PhD research; Interdisciplinarity
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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 | 0.014 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.021 |
| Science and technology studies | 0.010 | 0.016 |
| Scholarly communication | 0.020 | 0.011 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 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".