Bibliographic record
Abstract
Le Web 2.0 (ou médias sociaux) transforme notre façon de communiquer. Les modèles de communication unilatérale cèdent le passage à la conversation. Les musées oeuvrent désormais dans un environnement au sein duquel chacun est libre de créer et de fournir de l’information sur un sujet, même sur un sujet pour lequel les musées faisaient figure d’autorité par le passé. En relevant les défis que pose ce nouvel environnement, les musées rejoignent non seulement les publics grâce aux applications Web 2.0, mais ils les invitent à participer à cet acte de co-création. De nombreux musées interagissent avec les publics par le biais des technologies Web 2.0, notamment Facebook, Flickr, YouTube et Second Life, en plus d’utiliser des applications de médias sociaux à partir de leurs propres sites. Le présent article porte sur les technologies Web 2.0 utilisées par les musées, sur les défis et les possibilités associés à ces technologies à des fins sociales.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.012 | 0.016 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".