The birth of the Great Bear Rainforest : conservation science and environmental politics on British Columbia’s central and north coast
Bibliographic record
Abstract
This thesis examines the birth of the Great Bear Rainforest, a large tract of temperate rainforest located on British Columbia’s central and north coasts. While the Great Bear Rainforest emerges through many intersecting forces, in this study I focus on the contributions of conservation science asking: how did conservation biology and related sciences help constitute a particular of place, a particular kind of forest, and a particular approach to biodiversity politics? In pursuit of these questions, I analyzed several scientific studies of this place completed in the 1990s and conducted interviews with people involved in the environmental politics of the Great Bear Rainforest. My research conclusions show that conservation science played an influential role in shaping the Great Bear Rainforest as a rare, endangered temperate rainforest in desperate need of protection, an identity that counters the entrenched industrial-state geographies found in British Columbia’s forests. With the help of science studies theorists like Bruno Latour and Donna Haraway, I argue that these conservation studies are based upon purification epistemologies, where nature - in this case, the temperate rainforest - is separated out as an entity to be explained on its own and ultimately ’saved’ through science. Further, I posit that the scientific practices surrounding the Great Bear Rainforest are steeped in what I call protected area fetishism, in that they tend to mistake protected areas as a fixed, objective ’thing-in-itself’ necessary for biodiversity conservation. The overemphasis on protected areas enacted by conservation science obfuscates past and present relations contributing to the on-going reduction of biodiversity loss on the coast of British Columbia and elsewhere.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.022 | 0.012 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".