TURBULENCE IN MIRAMICHI BAY: THE BURNT CHURCH CONFLICT OVER NATIVE FISHING RIGHTS<sup>1</sup>
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract: A systematic technique is proposed for assisting in the design and implementation of policy and addressing the need to minimize or resolve disputes that may arise in the enforcement of regulations. The Graph Model for Conflict Resolution is a methodology that facilitates the modeling and analysis of interactive multiple participant‐multiple objective decision problems. In the problems considered here, decision makers and policy planners engaged in capacity building typically have different viewpoints over appropriate ways of developing options and enforcing policy choices. Incompatible understandings of resource potentials and limits, and disparities in utilization of these resources, exasperate stakeholders and make the capacity building process counterproductive and even conducive to conflict. A systematic conflict resolution technique is invaluable to policy makers and practitioners in defusing confrontations and reaching out for consensus among participants. In support of current approaches to policy planning and regulation, the Graph Model provides accurate predictions and strategic insights into shortand long‐term opportunities in multiple participant‐multiple objective decision situations. A conflict among the government of Canada, the Mi'kmaq First Nation, and commercial fishermen over the sharing of a natural resource in New Brunswick, Canada, is used to illustrate the advantages of this technique in practical problems.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it