On language and gender: An interview with Olivier Lallart about PD
Bibliographic record
Abstract
In this interview, I discuss with French director Olivier Lallart his film PD (or, in English, Fag) (2019). PD focuses on the sometimes-toxic-and-sometimes-romantic relationship between Thomas (Paul Gomérieux) and his schoolmate Esteban (Jacques Lepesqueur); and it offers thoughtful exploration of the language with which we describe same-sex love. The film has had a resoundingly successful second life on YouTube. Since its premiere, this 35-minute film has had more than 3.7 million views and it has been subtitled in over a dozen languages. In what follows, we discuss the film’s production – exploring issues ranging from casting to shooting, and from production costs to reception – and, more significantly, Lallart’s social commentary by means of Thomas’ and Esteban’s story. This interview advances scholarship both by attending to this film’s remarkably successful second life and by advocating for more critical attention to be directed to our use of language.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.024 | 0.013 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.006 | 0.012 |
| Insufficient payload (model declined to judge) | 0.006 | 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".