Anishnabe N’oon Da Gaaziiwin: An Indigenous Peacemaking- Mediation Nexus
Bibliographic record
Abstract
This article introduces a new dispute resolution process that we have termed a Hybrid Process, which has been designed to support nation-to-nation building in Canada. It is clear that classic theories and current mediation practices are not suited to conflicts that involve Indigenous peoples. In the past, we have used conventional mediation processes with First Nation People and it has not worked because mediation is not an Indigenous cultural practice. When conventional mediation has been employed, First Nation People have often not been participatory and have understandably withdrawn from the process. However, the mediation process is both malleable and adaptable, and the Hybrid Process is built on those solid foundations. A Hybrid Process refers to a combination of two culturally unique practices – Indigenous peacemaking and mediation. The combination of these two practices provides a culturally sensitive and holistic approach to conflict and nation building. This process has been designed for multi-party conflicts involving Indigenous leaders, communities, governments and stakeholders. Due to the complex nature of Indigenous relations in Canada, this process utilizes a team of culturally fluent practitioners to facilitate the process. Designed by a First Nations leader and former Grand Council Chief and two Canadian mediators, this process introduces a new perspective to resolving disputes in a changing landscape and incorporates what we have learned over many years and thousands of mediations.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.010 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".