Bibliographic record
Abstract
The Bon, the Bad and the Others: Some Remarks on the Phenomenal Success of Bon Cop, Bad Cop in Quebec This article discusses some aspects of the phenomenal box-office success in Quebec of Bon Cop, Bad Cop directed by Eric Canuel, released in 2006. Let me first refer to some statistics: within nine weeks or so from its release in early August of 2006, Bon Cop, Bad Cop was a few thousand dollars short of equalling the box-office success of Porky's, the all-time Canadian box office success from the early 1980s, a raunchy Florida-set sex-comedy that made 11.2 million in Canada. Ninety percent of the box-office, however, came from the home province ticket sales of Bon Cop, Bad Cop, leaving far behind such recent viewers' darlings as Les Boys from 1997, La grande seduction and Les invasions barbares, both from 2003 and above all, Seraphin, the historical drama from...
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.036 | 0.037 |
| Scholarly communication | 0.016 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.011 | 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".