MULTILEVEL DETERMINANTS AND PROCESSES OF INSTITUTIONAL CHANGE IN THE BRITISH COLUMBIA COASTAL FOREST INDUSTRY.
Bibliographic record
Abstract
This article discusses the multilevel determinants and processes of institutional change in the British Columbia coastal forest industry. Institutional change is attracting increasing attention among organizational scholars. Individual organizations change first, often stimulated by changes in the broader environment. Innovations are later mimetically adopted by other organizations under certain conditions. Within an organization, the need for change is noticed and championed by an individual or team, and the adoption of change requires adjustments in the interpretations of other organization members. For years in British Columbia, environmentalists and forest companies engaged in a War of the Woods. Environmentalists protested clearcutting (a logging practice in which all of the trees in an area are cut), by blockading roads and chaining themselves to logging equipment. Clearcutting was institutionalized by practice, by legislation, and normatively. Forest companies staunchly defended clearcutting as tree farming, the safest way to log, and the only way they could stay in business. In 1998, forest company MacMillan Bloedel (MB) shocked its industry and stakeholders, and earned environmentalists' accolades, when it announced it would completely replace clearcutting with variable retention logging. MB subsequently pressured other firms to adopt variable retention and negotiate with environmentalists. Several of the largest companies did, and the institutional environment changed radically.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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".