Bibliographic record
Abstract
A central contention of this paper is that conservation strategies are failing because they have become increasingly integrated into, and share the assumptions of, the structures of capitalism. As a result, conservation is becoming a strategic specialty within capitalism, rather than an ethical challenge to its basic assumptions. The paper examines this integration by analysing the way Hardin’s argument in the “tragedy of the commons” metaphor was taken up by policy makers in Canada’s East Coast fishery and a case is made that, as seen in the case of the fishery, this strategic integration limited the analytical capability of conservation to highlight the causes of environmental degradation. The critical literature on Hardin’s model points to the failure to recognize the importance of social relations and local institutional arrangements in combatting environmental failure. This paper contributes to the importance of “the social” in conservation debates by emphasizing Polanyi’s contrasting definitions of formal and substantive economics and the way they relate to contrasting conceptions of tragedy, as set out by Hardin (formal tragedy from above) and Goldmann’s conception of a historically specific tragedy that can be described as substantive tragedy from below. The analytical failure associated with Hardin’s metaphor can serve as a cautionary tale for current strategic and specific conservation strategies that tend to downplay the importance of ethical and social issues.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.012 | 0.085 |
| Scholarly communication | 0.014 | 0.015 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".