Quelles (re)productions de normes identitaires dans YouTube? Étude de chaînes LGBTQIA+ au Canada
Bibliographic record
Abstract
Contexte : Cet article étudie les thématiques abordées dans des chaînes YouTube LGBTQIA+ au Canada, ainsi que les normes identitaires qu’elles contribuent à (re)produire. Analyse : L’analyse (N = 941 vidéos) révèle une répartition genrée des thématiques et une rupture avec le gender gap dans YouTube, alors que les chaînes les plus populaires appartiennent à des YouTubeuses trans. Conclusion et implications : Malgré une reproduction de l’hétéronormativité, les vidéos contribuent à l’élargissement de certaines normes identitaires et constituent une alternative aux discours médiatiques dominants. Le tri algorithmique de YouTube n’est pas étranger aux résultats obtenus relatifs à la reproduction de normes dominantes.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".