Entre maladresse et authenticité : la recherche du plaisir dans <i>Mrs. Fletcher</i>
Bibliographic record
Abstract
Dans les nouvelles formes de sérialité télévisuelle se dégage une figure de personnages de femmes qui se trouvent en décalage avec la norme, grotesques, dissidentes : cet article propose de se pencher sur un personnage en particulier, la protagoniste de la série Mrs. Fletcher . Cette série de HBO, à cheval entre comédie et drame, met en scène la découverte de la pornographie par une femme de 45 ans, rôle joué par Kathryn Hahn. En analysant la représentation du désir et de la transgression présente dans cette série, nous aborderons l’idée d’un plaisir qui devient forme de connaissance et proposerons une piste de lecture de la sérialité contemporaine à l’aune de la maladresse et de l’authenticité.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.056 | 0.002 |
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; both teacher heads agree on what is shown here.
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".