Acknowledgments...........................................
Bibliographic record
Abstract
All rights reserved. This thesis may not be reproduced in whole or in part, by photocopy or other means, without the permission of the author. In recent years, reconciliation has evolved as a potential approach to address First Nations-Canada conflicts. However, there has been no comprehensive study of what reconciliation means or entails. This thesis suggests the heart of reconciliation is essentially a parallel process of personal and political transformation from systems of domination to relationships of mutuality. It also suggests four guiding touchstones to create conditions for reconciliation: drawing on the hdarnental worldviews of the parties themselves, transcending the victim-offender cycle, engaging in large-scale social change, and assessing appropriate timing and tactics. As a relatively new field, reconciliation calls for a research design which stresses the importance of aligning methodology with a given research topic as a way to produce what Patty Lather has called "emancipatory knowledge. " Consequently, the four guiding touchstones became the methodology. As this thesis explores in greater detail the role worldviews play in creating conditions for meaningful reconciliation it emphasizes the important connections between the role worldviews play in human survival, the global loss of meaning, and violence today. Three main worldviewing skill sets are then described in fuller detail: 1) connecting parties to their fundamental worldview; 2) learning to engage across worldview difference, 3) regener tin Indigenous cultures and re-civilising Western cultures. A
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.138 | 0.096 |
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".