Reallocating a Regional Fishery Resource: Restoring Aboriginal Fisheries on the Upper Skeena, British Columbia
Bibliographic record
Abstract
"The discussion in this paper will focus on two major considerations that need to be addressed In assessing the Gitksan-Wet'suwet'en claim. One is the question of equity. This involves exploration of the historical basis for the Gitksan-Wet'suwet'en claim to a larger share of the Skeena salmon resource than is currently available to them. It also concerns the implications of any reallocation of current harvest entitlements, with respect to claims for compensation by other user groups which may be disadvantaged by the reallocation. What is 'equitable,' of course, in the final analysis is a matter of subjective judgment. However, given that there are some widely held common notions of equity, the facts of the case may be left to speak for themselves. \n \n "The other major consideration to be explored is that of the overall economic consequences of a reallocation in favor of the Gitksan-Wet'suwet'en. Much will depend on the nature of the management regime that will be developed in implementing the reallocation. The paper will explore opportunities to use the implied changes in harvesting patterns to improve sustainable catches and net returns. I have neither the extensive data base nor the time and resources necessary to carry out an exhaustive cost-benefit analysis that would be required for refined estimates. However, enough general information is available on the fishery to allow some general conclusions to be drawn on the basis of informed speculation."
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".