Attitudes of disposability towards MMIWG on the highway of tears
Bibliographic record
Abstract
Missing and Murdered Indigenous Women and Girls has been a common topic in the media for the past few decades, and the Canadian government and Canadian people are beginning to recognize, realise and uncover the truths behind the continuing epidemic of Indigenous women identifying and LGBTQ2+ being victimised and murdered all over the country. As the cause is gaining attention, it is important to take the time to understand why thousands of Indigenous Women and Girls have gone missing or have been found murdered with little to no attention from police, society, or the media. This project connects the relationship between “disposability” and “MMIWG”, and then implements the relation onto the case study of the Highway of Tears, using CPTED to provide a concrete direction of application for future use. The research is found by using a semi-systematic literature review and case study approach using online journal tools and examining the contents for similar relationships and findings. A clear equation can be formulated to understand how MMIWG has grown exponentially with little knowledge to the greater public. Society finds certain behaviours as “risky”, and these behaviours come with predetermined consequences that are accepted as a punishment. Therefore, if Indigenous women partake in societally deemed “risky” behaviours, and if they face violence, it is deemed as an acceptable punishment, therefore when it is taken to the police there is less help provided due to the preconceived notions that the violence is the result of the “risky” behaviours, versus the Indigenous women being a target of violence. This project utilises a CPTED study on the Highway of Tears in order to create recommendations to make the space safer. The results found that there was a lack of defensible space, light and the environment inhibits communities to be key agents in their own safety, which speaks to the rates of MMIWG on the highway. Keywords: MMIWG, Highway of Tears, Disposability, CPTED.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".