Canadian panopticon: a feminist and postcolonial reading of the niqab and murdered and missing Indigenous women inquiry debates during the 2015 federal election
Bibliographic record
Abstract
Canada is a settler-colonial state that specially targets and others minority groups, such as Indigenous peoples and recent immigrants. This was no more apparent than during the 2015 federal election, which saw debates on whether to ban Muslim women from wearing niqabs and other head coverings and whether to hold an inquiry into the epidemic of missing and murdered Indigenous women. By examining excerpts from speeches, tweets, articles, and interviews made by politicians, citizens, and journalists, this thesis traces the shape of settler-colonial systems and their impact on Indigenous and immigrant women. Canadian society demands conformity to sexual and cultural norms that require walking a tightrope of these double-edged ideals. Conformity is maintained through societally enforced regimes, known as the Panopticon, where each individual is both prisoner and guard. This constant surveillance does not simply end there, however, as Canadian settler society has different gender structures and norms for both men and women: women are subject to far stricter social expectations than men and, as this thesis brings to light, women in minority groups, such as indigenous and Muslim women, fall under an even harsher Canadian spotlight.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.049 | 0.023 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.009 | 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".