Old growth forest preservation in British Columbia and the American Pacific Northwest : an account of a debate for survival
Bibliographic record
Abstract
This essay offers a study of old growth forest policy in British Columbia and the American Pacific Northwest and, in so doing, attempts to contribute to the sparse comparative environmental literature that uses Canada as a case study. Specifically, the essay addresses the question of why old growth forest preservation policy divergences so dramatically between British Columbia and the American Pacific Northwest. After establishing that American Pacific Northwest and British Columbia old growth forest preservation policy diverges, the author employs a chronological methodology to reconstruct the current old growth preservation policy outcomes in both jurisdictions. The author then identifies a series of variables that affect old growth forest preservation policy in both jurisdictions, and examines each as a force of divergence. The essay discusses the different influences of two non-institutional variables-science and economics-and two institutional variables-federalism and legalism-on American Pacific Northwest and British Columbia old growth policy. The essay concludes by discussing the question of how each variable works with one another to produce this instance of policy divergence. The author finds that all four variables collaborate with one another and contribute to the divergence. However, the essay concludes that the major determining factor in this case of policy divergence is the interplay of the two institutional variables.
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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 | 0.006 |
| Science and technology studies | 0.025 | 0.015 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".