Bibliographic record
Abstract
La réalité des musées québécois éloignés des grandes agglomérations urbaines diffère substantiellement de celle des institutions évoluant en milieu métropolitain. Meggie Savard définit l'environnement dans lequel évoluent ces institutions en évoquant une certaine forme d’autonomie culturelle, la présence d’une forte identité régionale et leur composition démographique (à prévalence caucasienne, homogène et francophone), le phénomène de l’exode rural, un faible niveau de scolarisation des habitants ainsi qu’un taux de chômage supérieur à la moyenne nationale. Malgré les difficultés avec lesquelles ces musées doivent composer, les divers paliers de gouvernance local, provincial ou national ne leur accordent aucune reconnaissance ni statut particulier. En s’appuyant sur ce constat, Meggie Savard tente de définir et de circonscrire le « musée régional » en l’opposant au musée urbain par le biais d’une revue d’écrits et l’étude d’un cas typique observé au Saguenay–Lac-Saint-Jean afin de proposer quelques idées d’appui financier adaptées aux besoins propres à ces institutions.
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.009 | 0.010 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.000 |
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.
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".