Bibliographic record
Abstract
Bringing together case studies from Canada, the Nordic countries and Russia, this book is the first to provide a comparative examination of the current transformations in the forest industry regimes and the challenges they make for the communities dependent on this industry. Questioning how globalization has influenced forest regimes, the book focuses on individual forest companies and argues that they are the main motors of the industry's internationalization, often without taking due consideration of the complex interrelations between society, the environment and forest trade. During the current phase of globalization, the sphere of material production within the forest industry has increasingly been modified by more speculative signals from the market. Both the growing role of investor interests, as well as the broader societal demands for 'greening' the production chain, have forced managers to be more sensitive to the performance profile and image of their companies. In conclusion, the book highlights instances of processes working towards homogenization and diversity, and suggests that while Anglo-American management practice is increasingly important across the northern forest regions, it is also meeting with resistance due to historical and political conditions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.015 | 0.016 |
| Scholarly communication | 0.010 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".