From fur to fir: Lessons for the BC forest industry from the anti-fur campaign
Bibliographic record
Abstract
BC's forest industry is feeling internal and international pressure to change its practices, and there is an increasing move to certification, amidst debates about preferred certification modes. This reflects changes in the economies of many of Canada's rural and northern communities, which have traditionally been dependent upon natural resources, but are now coming under pressure from the global community – not only in economic terms, but in terms of social values. As demography changes, and with it, social and economic values, this pressure is likely to continue. The Canadian North first felt such pressure as a result of the European boycott of the Newfoundland seal hunt, and then anti-trapping boycotts that have occurred periodically since then. These campaigns have had a profound effect on the lifestyles, cultures and sustainability of the northern communities. Over almost three decades, the government, non-government organizations and people of the North have had to learn to deal with and respond to these external campaigns that threaten them. The lessons they have learned about the nature of these campaigns could be useful to the province of British Columbia, which is now coming under increasing pressure from Europe and the US regarding its forestry practices. This paper outlines the evolution and characteristics of the international campaigns against sealing and trapping, as well as the experiences of northerners in dealing with them. It goes on to apply these lessons to the BC situation, with some recommendations for appropriate responses. Fundamentally, these campaigns reflect changing demographic and social characteristics and values in North America and Europe, and the changing relationship of people to natural resources, but they also raise questions about fair reflection of the variety of stakeholder interests in resource decision-making, and the limits on definition of "stakeholders." Key words: Boycotts, resource use
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.026 | 0.007 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".