Brèves remarques à propos d'une approche ethnologique du musée
Bibliographic record
Abstract
. S’inscrire dans la marge1 En 1997, on soulignait le cinquantieme anniversaire des etudes de folklore a l’Universite Laval, a Quebec. A cette occasion, Roland Arpin, directeur general du Musee de la civilisation de 1987 a 2001, prononca une conference dans laquelle il presenta les methodes d’exposition et de collecte pratiquees dans son institution. Il y aborda plus particulierement la relation de ce musee de societe quebecois avec les temoins de la culture contemporaine. Pour conclure son expose, il ajouta : « Peut-etre qu’un jour prochain, il se trouvera quelqu’un parmi vous pour faire l’ethnologie des musees de la fin du siecle2. » Ainsi formulee, la phrase ressemble a une invitation. Or, a quoi referait Arpin precisement? S’agissait-il d’un simple clin d’œil lance aux ethnologues presents dans la salle pour terminer sa communication ou d’une veritable incitation a poursuivre les recherches en ce sens? C’est a la lecture de l’article tire de cette conference que nous avons commence a nous interroger sur cette possible ethnologie du musee suggeree par Arpin et qui guide aujourd’hui notre reflexion de jeune ethnologue et de doctorante en museologie3. La multidisciplinarite, qui definit la museologie actuelle et qui conjugue les approches, les interets de recherche, les ecoles de pensee, les methodes et les differentes conceptions du musee, permet cette interaction entre etudes museales et ethnologie. Cette derniere representant notre attache disciplinaire, nos recherches d
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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 | 0.010 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.018 | 0.030 |
| Scholarly communication | 0.017 | 0.014 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".