Bibliographic record
Abstract
This article focuses on three recent films by women directors and produced in Quebec that feature as their main subjects First Nations characters who reside in various corners of the province: Québékoisie (2014), a road documentary directed by biologists-turned-film-makers Mélanie Carrier and Olivier Higgins; Avant les rues/Before the Streets (2016), the first full-length fiction film in the Atikamekw language by screenwriter and director Chloé Leriche; and Le Dep (2015), a psychological drama by Mohawk-Québécois film-maker Sonia Bonspille Boileau. The first two films were shot mainly on Indigenous soil (the first on several Innu reserves of the Côte-Nord; the second in the Atikamekw Community of Manawan), while Le Dep takes place in a fictional Innu community and was filmed in the rural Outaouais region. In addition to offering an analysis of these understudied works, the article situates them within a corpus of other Québécois films featuring Indigenous characters and considers them through the wider lens of cinéma-monde.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.035 | 0.022 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.018 | 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".