Sustaining the Forests of the Pacific Coast
Bibliographic record
Abstract
Forests define the Pacific Coast in many ways. Culturally they are part of the traditions of the First Nations; economically they have sustained an industry that has created settlements and wealth throughout the area. In the last twenty years, the forests have become the subject of increasing conflict, as economic interests clash with changing social and political values. The war in the woods has escalated, hardening battle lines and polarizing forest politics. In this thoughtful collection of essays edited by Debra J. Salazar and Donald K. Alper, forest policy in the U.S. Pacific Northwest and British Columbia is examined in a binational context. While US and Canadian forest policy and forest management approaches differ, the two countries face similar challenges and conflicts. Contributors discuss the evolution of forest exploitation, the response of timber companies to U.S. federal environmental regulations, sovereignty for First Nations communities, and the reshaping of the political economy of forests by global forces on both sides of the border. Groups usually ignored in the forest policy debate -- such as First Nations peoples, workers in the emerging non-forest economy, and citizen activists -- are also given voice in this fascinating compilation. The contributors to Sustaining the Forests of the Pacific Coast offer new perspectives that recognize the complexity of the issues and the diversity of interests in forest politics. A valuable contribution to the ongoing debate over forest policy on both sides of the Canada/U.S. border, these essays analyze the challenges facing forest policy makers and open the discussion up to those whose voices have not been heard before.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".