Introduction: Audiovisual Responses to the Polytechnique Massacre
Bibliographic record
Abstract
The symbolic resonance of the brutal murder of 14 female students at the engineering college of the Université de Montréal on December 6, 1989 has been profound and lasting in Quebec, in Canada, and internationally. The Introduction to this special issue highlights key theoretical arguments that have evolved around the audiovisual legacy of the Montreal Massacre and the political and ethical issues implicated in the representation of historical trauma. Contextualizing the complex audiovisual legacy of the event, this short introductory essay points to the diversity of approaches taken in the essays and documents that follow, which include an interview with Quebec journalist Francine Pelletier, an in-depth study of the politics of witnessing in documentary films and videos focusing on the event, four distinctive essays on Denis Villeneuve's 2009 feature Polytechnique and a cine-documents section which includes selected contemporary reviews of Villeneuve's film.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".