Bibliographic record
Abstract
Quel(s) regard(s) les musees de societe posent-ils sur les societes ? Le musee fait partie des institutions structurantes d’une societe, notamment par son role de creation et de partage de savoir : en ce sens, il est a la fois miroir d’une societe et lien critique. Preoccupes par les enjeux contemporains tels que la diversite culturelle, la numerisation, la mondialisation, le developpement des activites culturelles ou encore le developpement durable, les musees de societe doivent sans cesse s’adapter, creer et innover en jonglant avec les paradoxes inherents a toutes civilisations. A travers des exemples francais et quebecois, cet article presentera un point de vue critique sur les defis et les enjeux des transformations operant au sein des musees de societe, que ce soit au niveau du discours tenu sur la diversite culturelle, de la mise en museographie de l’autre, de la mise en valeur du patrimoine materiel et immateriel ou encore de l’engouement grandissant des visiteurs. Du fait de sa mission et de part sa dynamique, le musee de societe ne serait-il pas le point de bascule qui permet d’offrir une lecture integree des societes ? Si oui, quel monde souhaite-t-il construire ? De quel monde souhaite-t-il etre temoin ?
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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.026 | 0.034 |
| Scholarly communication | 0.016 | 0.011 |
| Open science | 0.003 | 0.018 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.027 | 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".