Bibliographic record
Abstract
D’après de récentes recherches, les fanfictions seraient indissolublement et exclusivement une manifestation linguistique et un fait de l’écrit. À l’inverse, images ou vidéos sont traitées comme des productions ancillaires ou comme des ornements hasardeux, non comme des créations intentionnelles et assumées. Pourtant, les fanfictions audiovisuelles existent bien et elles sont même des manifestations d’une littératie multimodale. Cet article analyse donc les réticences qui expliquent ce décalage théorique, à travers un examen historique puis épistémologique. Il montre ensuite quels effets de légitimation ont pu encore biaiser la conception des fanfictions. À travers un corpus de fanvidéos, il fait la preuve que les fanfictions sont pleinement des moyens d’expression de soi au sein d’un fandom et montre à quel point la narration audiovisuelle peut s’avérer un précieux outil de production et d’interprétation.
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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.017 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".