Bibliographic record
Abstract
Robin Aubert’s 2017 film Les Affamés is a zombie genre film, set in an unspecified region of rural Quebec. The first Quebecois addition of note to the zombie film genre, Les Affamés follows the few remaining humans who have avoided contamination from their infected, flesh-eating pursuers. The rustic setting provides a haunting backdrop as the protagonist, a bearded science-fiction devotee named Bonin, and his five companions, attempt to flee through the woods to safety, pursued by a screaming, blood-thirsty horde of their former friends and neighbors. Les Affamés functions in large part as an allegory for rural poverty and economic isolation. Decaying farmhouses, rusting tractors, and an abandoned mine are just a few of the iconic images that invoke the real-world struggles of once-healthy agricultural and mining communities in a twenty-first-century neo-liberal economy. This paper will focus in particular on the zombie as an avatar for Quebecois and, more broadly, North American rural decay, noting how Aubert uses a zombie virus as an allegory for depopulation and economic marginalization. Indeed, the Affamés of the film’s title also suggest the ravenous appetites of a capitalist system which, like the film’s titular flesh-eating monsters, appears insatiable.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.004 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.022 | 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".