Social Denial: An Analysis of Missing and Murdered Indigenous Women and Girls in Canada
Bibliographic record
Abstract
Understood sociologically, denial is best conceptualized as a social practice. As a phenomenon, social denial refers to patterned behaviour where actors both know and do not-know about uncomfortable truths (Cohen, 2001). Put simply, social denial is a socially reproduced blindness in the face of traumatic events and processes. In opposition to social denial is a different social practice, bearing witness. Bearing witness is engaged when society’s actors give voice to those who would otherwise be silent. Drawing on theoretical frameworks from Stanley Cohen’s work States of Denial and Fujiko Kurasawa’s work Global Justice, this thesis aims to critically reflect and explore the registers and mechanisms of both social denial and bearing witness. The exploration of social denial is sociologically relevant, and generally important, as a means for understanding the role it plays in society, and to further understanding what social denial is and how it works. The better actors understand an issue the more capable they are of addressing it. This thesis conducts a media frame analysis of selected published articles from the National Post and the Globe and Mail that speak to the issue of MMIWG. This analysis reveals social denial through the frames “culpable victim”, “poster child”, and “the extra”; and bearing witness through the frame of the “honourable victim”. The analysis and research of this thesis reveal how social denial covers up the relevance of colonialism with respect to MMIWG. Furthermore, it suggests that social denial acts to both camouflage the gritty details underlying MMIWG and erase the identities of MMIWG.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.021 | 0.010 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".