USING WETIKO LAWS TO ADDRESS LATERAL VIOLENCE IN THE WORKPLACE: APPLICATION OF THE INDIGENOUS LITERARY-LEGAL POLICY ANALYSIS FRAMEWORK
Bibliographic record
Abstract
My dissertation is broadly about organizational Indigenization and Indigenous law. My primary research aim is to explore how Cree law, specifically wetiko law, can be used to critically assess existing Indigenized Occupational Health and Safety (OH&S) policies. These OH&S policies relate to conflict management and lateral violence resolution in workplaces with Indigenous, settler, and new immigrant staff. As part of my primary research aim, I created a methodology for finding Indigenous law and engaging in critical policy analysis: the Indigenous Literary-Legal Policy Analysis Framework (ILLPA framework). As demonstrated within this dissertation, the ILLPA framework draws together Indigenous literary analysis and Indigenous legal work in a unique way to create a new framework for analyzing governance policies. The ILLPA framework incorporates an Indigenous literary analysis model as a sub-method, which is applied to contemporary Cree literary texts to identify contemporary understandings of wetiko laws that can then be compared to traditional understandings. In addition, the ILLPA framework expands the case briefing methodology (Borrows, J., 2010; Friedland, 2012; Napoleon & Friedland, 2015-2016) used in Indigenous legal studies by incorporating a holistic and gendered theoretical approach to view Cree law through a critical lens. By using the ILLPA framework, I was able to critically analyze OH&S documents from two organizations in Alberta, Canada that identified Cree law within their toolkits or policies. The ILLPA framework was used to assess how effective these organizations were at incorporating Cree law into organizational governance. Analysis indicated that the Government of Alberta Miyo Pimatisiwin Health and Safety Tool Kit (2023), which implicitly draws on the Cree legal principle of miyo pimatisiwin, uses Cree law in a superficial manner, while the University nuhelot’įne thaiyots’į nistameyimâkanak Blue Quills Student Complaint & Grievance Procedures (2021), which explicitly draws on Cree Natural Law, incorporates Cree law in a more meaningful way. My dissertation demonstrates that by drawing Indigenous literary and legal analysis into a single framework, a rich method for policy analysis emerges. The ILLPA framework can identify specific Indigenous legal principles, changes over time in how those legal principles are understood, and overarching themes, such as gendered perceptions of Indigenous legal traditions and contemporary perceptions of community.
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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 | 0.019 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.015 | 0.037 |
| Scholarly communication | 0.016 | 0.010 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.004 | 0.005 |
| 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".