Lost at Sea or Charting a New Course? Mapping the Murky Contours of Cinéma-monde in Floating Francophone Films
Bibliographic record
Abstract
In order to demonstrate some of the multiple nodes that must be considered in any construction of a meaningful theory of ‘cinéma-monde’ (production, narrative, economic context; the migration of films, filmmakers, and actors), this chapter explores floating ‘francophone’ films. In these films, cinéma-monde is not mapped exclusively along the boundaries of French-speaking countries, regions, or zones, nor is it exclusively extra-Hexagonal. These ‘boat films’ are set on small vessels (L'iceberg by Dominique Abel, Fiona Gordon and Bruno Romy, 2005, Belgium) and freighters, which circulate goods but also people and languages – Diego Star (Frédérick Pelletier, 2013, Canada/Belgium), and Fidelio, l'odyssée d'Alice (Lucie Borleteau, 2014, France) – or narrate the perilous crossing by sea to European territory, as in Harragas (Merzak Alouache, 2009, Algeria/France) and La pirogue (Moussa Touré, 2012, France/Senegal/Germany). This chapter theorizes sea voyages for work and migration within the context of contemporary border theories, North-South migration debates, and cinematic production networks.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".