"ALL RIGHTS MATTER": A CRITICAL EXAMINATION OF THE ONTARIO HUMAN RIGHTS COMMISSION'S SYSTEMIC CHANGE INITIATIVES IN
Bibliographic record
Abstract
This dissertation examines the Ontario Human Rights Commissions (OHRC) partnership engagement with police services via the use of voluntary Project Charter agreements. Through an analysis of OHRC policy documents spanning from 1962 to 2016, qualitative research with three municipal police services (Ottawa, Toronto, and Windsor) and the OHRC, utilizing methods developed out of the epistemological insights and normative commitments of Critical Race Theory, Feminist Political Economy and Critical Policy Studies, the analysis centres on the duality of law and the race-neutral logics that work to constrain the viability of human rights-driven anti-racist structural change.\nThis work engages the notion All Rights Matter to describe a flattened approach to human rights that restricts focussed consideration of the operation of structural racism. The All Rights Matter approach employed within these voluntary Project Charter agreements obfuscates areas of institutional inaction or resistance and deflects attention away from inaction, or failure, toward addressing structural racism and community concerns of racial profiling and misuse of force. This flattened approach to difference is intimately connected to a diversity management posture favouring business vernacular and rationales over equity.\nThe five chapters comprising the dissertation reveal the emancipatory limitations of rights claims vis-a-vis racism in particular within the Ontario context. Chapters one and two offer theoretical and historical background to the All Rights Matter approach. Chapter three attends to the role of policing in reproducing a racially inequitable social order, the OHRCs partnership-oriented adoption of diversity management, and the settlement agreement that brought about the Ottawa Police Race Data Collection Project. The case studies of the Toronto and Windsor police services examined in chapters four and five illustrate how these partnerships with the OHRC serve as containment strategies, quelling public pressure to address racism within these services.\nBy way of conclusion, the dissertation underlines the importance of severing human rights approaches from a diversity management framework that extracts value from racialized groups without addressing inequitable racial orders and the pressing need for human rights accountability and legally-enforceable public interest remedies.
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 | 0.044 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.061 | 0.111 |
| Scholarly communication | 0.021 | 0.012 |
| Open science | 0.004 | 0.011 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.003 | 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".