Contrasting visions in le jeune cinéma: poetics, politics and the rural
Bibliographic record
Abstract
AbstractNorthern France and Flanders form what Jacques Brel named ‘le plat pays’ (‘the flat country’). This region, which has not traditionally been the focus of popular cinema, has in the 1990s seen the emergence of a ‘cinema nordiste’ (Northern cinema). Bruno Dumont is perhaps the most acclaimed director of this cinema, but other examples include both well-known directors such as Bertrand Tavernier (Ca commence aujourd'hui (1999)) and first-timers like Thomas Vincent (Karnaval (1999)). The characteristics of Dumont's work have been widely discussed (see Bruno Dumont, edited by Sebastien Ors). The cinema of Benoit Mariage, though not as well known, is placed in a similar cultural context, just across the border in Belgium. Both directors film in a rural environment, using non-professional actors. Despite the similar background to the work of Dumont and Mariage, there are sharp differences between the representations of these two directors. Dumont is a crude realist with a quasi-ethnographic perspective; ...
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.020 |
| Scholarly communication | 0.010 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".