Féminicide autochtone au Canada : représentations médiatiques d'une violence passée sous silence
Bibliographic record
Abstract
This present master thesis focuses on the sociological phenomenon of violence affecting Aboriginal women in Canada, specifically what may be apprehended through an intersectional perspective on violence Aware that the silence surrounding this phenomenon is just as violent as the situation itself, this thesis proposes tools for understanding and reading that allow everyone to better understand the ins and outs of the manifestation of this violence. This analysis explores how the invisibility of these women in society takes shape, how it is expressed, and what it reveals about the Quebec and Canadian society. It was decided to address our problem through the written press media and the production of mediatic and journalistic discourses, which often reveal a particular ideology and themselves reflect a society in general. Using a corpus of 200 articles with different themes, and in light of certain concepts related to discourse analysis, the results of our data will allow us to discuss the influence of these mediatic and journalistic discourses, and better understand the government issues, particularly Aboriginal ones, facing the country today. We will thus see how media power can play a significant role in society and how indigenous women are increa singly becoming part of an empowerment movement, enabling them to deconstruct the social barriers in which they have long been partitioned.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.017 | 0.012 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".