Second Life comme espace de sociabilité pendant la pandémie de COVID-19
Bibliographic record
Abstract
Les mondes virtuels et les jeux en ligne ont connu une remarquable croissance en termes de fréquentation dans les premiers mois de la pandémie COVID-19. Nous discutons ici de l’utilisation de Second Life comme espace de sociabilité dans ce contexte. Partant de notre recherche ethnographique nous présentons quelques hypothèses pour expliquer comment ce type de plateforme en ligne est privilégié au détriment d’autres, notamment dans la situation de distanciation physique vécue dans plusieurs pays. Une analyse centrée sur les caractéristiques sociotechniques de cet environnement numérique, ainsi que sur les expériences vécues par ses utilisateurs, nous permet de proposer l’immersion, la corporéité des avatars, la synchronicité et la persistance de ce monde comme éléments distinctifs de l’attraction exercée aujourd’hui par ce type de plateforme.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".