Affronter le confinement grâce à la modalisation des défilés de<i>RuPaul’s Drag Race</i>dans<i>Animal Crossing: New Horizons</i>
Bibliographic record
Abstract
Le succès instantané que connutAnimal Crossing: New Horizonsau début de la pandémie, en mars 2020, incita plusieurs chercheur⋅se⋅s à se demander dans quelle mesure ce jeu servit, pour certain⋅e⋅s joueur⋅se⋅s, de remède aux désagréments causés par la pandémie, grâce à son environnement et son avatar modulables favorisant notamment la liberté de création, les interactions sociales et l’expression identitaire. Cet article illustre ces diverses fonctions positives jouées parAC:NHdurant la pandémie et les paramètres du jeu qui les rendent possibles à partir d’une étude de cas, soit celle de l’organisation, par un joueur nommé Jou, d’un défilé en hommage à l’émissionRuPaul’s Drag Racesur son île durant le confinement.Cette étude de cas s’appuie sur l’analyse de son récit phénoménologique et l’analyse du matériel produit durant l’évènement à la lumière de la théorie des cadres de Goffman et des théories sur la performance de Goffman et Butler.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".