Operationalizing TRC #92 and UNDRIP: Evaluating the Effectiveness of Moral Suasion (Ethical Appeals) in Saskatchewan Credit Unions’ Policies and Practices
Bibliographic record
Abstract
This thesis explores Saskatchewan credit unions' responses to the 2018 Canadian Credit Union Association (CCUA) resolution, which promotes the adoption of Truth and Reconciliation Commission’s Call to Action #92 (TRC 92) and the United Nations Declaration on the Rights of Indigenous Peoples (UNDRIP) as frameworks for reconciliation with Indigenous Peoples in Canada. I investigate the usefulness of ethical appeals known as moral suasion and how the tool operates as a soft policy instrument. Specifically, I use these Indigenous frameworks to examine how moral suasion influences credit union governance and operations when no formal enforcement systems, such as laws or incentives, are in place. The research design employs a qualitative multiple-case study approach to investigate TRC 92 and UNDRIP operationalization at two Saskatchewan credit unions: Affinity and Synergy. I analyze institutional documents alongside semi-structured interviews to determine how leadership, resources, and geographical factors influence organizational approaches. The research uses thematic analysis to analyze stories within and between the two case studies. The study shows that moral suasion can support institutional reform in values-based institutions; however, its overall usefulness is limited without national standards or sector-wide structural supports. This research enhances policy discussions by evaluating moral suasion's operational limitations and strategic potential as an unenforceable policy instrument. The application of moral suasion is seen in monetary policy and in areas that determine institutional conduct regarding matters of morality or ethics, including public health, environmental sustainability, and corporate social responsibility. In the context of Indigenous reconciliation, the research further demonstrates the capacity of moral suasion to enable the advancement of ethical reforms in Canada's financial co-operative sector despite the absence of regulatory requirements or sector-wide enforcement mechanisms.
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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 | 0.030 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.015 | 0.021 |
| Scholarly communication | 0.012 | 0.003 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".