Les épisodes autonomes : écarts formels et narratifs dans The X-Files et Buffy The Vampire Slayer
Bibliographic record
Abstract
Les genres télésériels évoluent depuis l’émergence du médium, ils se raffinent, se complexifient, s’hybrident, répondant aux exigences et aux compétences spectatorielles grandissantes de son public. Les genres permettent ainsi l’émergence de formules, que l’on adopte pour mieux se les approprier, et à partir desquelles les créateurs peuvent construire la matrice qui donnera à leur œuvre sa structure unique. Entre les séries canoniques des débuts et les grands feuilletons d’aujourd’hui, les années 1990 ont donné naissance à plusieurs séries hybrides, notamment dans le sous-genre du fantastique (par exemple, The X-Files et Buffy The Vampire Slayer), qui combinent des épisodes sériels et feuilletonnants. Au cœur de ces séries se trouvent des épisodes autonomes, souvent les plus appréciés, qui s’écartent de la matrice et proposent des innovations ou des jeux fictionnels, narratifs ou transtextuels.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.002 |
| 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".