Of Fish and People: Managerial Ecology in Newfoundland and Labrador Cod Fisheries
Bibliographic record
Abstract
This dissertation aims to understand the history of, and possible alternatives to, managerial responses to socio-ecological issues by examining one of the largest natural resource management failures of the twentieth centuryâthe collapse of the Northern cod fisheries off Newfoundland and Labrador, Canada. In 1992, the Northern cod fishery off Newfoundland and Labrador (the world's largest ground fishery) was shut down. The Northern cod had been reduced to 1% of their historic spawning biomass and cod fishing as a way of life had come to an end after a 500 year history. The dissertation develops and applies a critical theory of managerial ecology to explore the history and consequences of managerial ideas and interventions into the cod fisheries. It argues that managerial ecology is deeply implicated not only in leading to the collapse of the cod fisheries and the failure of cod stocks to recover, but also in creating new ecological and social problems that cannot be solved by new and improved managerial designs. The dissertation describes the ascendance of managerial ecology within Newfoundland and Labrador cod fisheries beginning with the history of the birth of the fisheries management idea and its development up to the 1992 moratorium on cod fishing. Developments post-1992 are then presented, emphasizing the tendency of politicians, bureaucrats and academic researchers to offer innovative managerial strategies for the cod fishery rather than calling into question managerial relationships themselves and proposing fundamental alternatives. It illustrates how under post-92 reforms, cod have become managed as elements in complex ecosystems as opposed to single species populations; how traditional fishers who want to continue fishing are required to become self-managing professional fish harvesters; and how industrialists and government bureaucrats promote the idea that the wild cod fishery should be replaced by industrial fish farming. The dissertation concludes with a reflection on the development of managerial ecology in the face of natural resource collapse. Suggestions are made for future research directions in environmental studies that move beyond managerial ecology by focussing on lessons emerging from complex ecosystem science that challenge the efficacy of management as well as normative-political arguments that question its legitimacy.
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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 | 0.000 | 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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".