Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The forest sector, historically Canada's largest industry and largest employer, remains today the source of most of Canada's positive balance of trade on goods and commodities. Why, then, is there a dearth of policy literature devoted to exploring the industry as a nation-wide phenomenon? Arguing that the complexity of policy-making in the forest sector has led many analysts to focus exclusively on specific sectoral activities or jurisdictions, this collection of essays offers a simplifying framework of analysis developed in comparative public policy studies to address the current status of Canadian forest policy nationwide. Using case studies of historical and contemporary federal and provincial forest policies, the essays examine the manner in which changes in resource management ideas, subsystem membership, industrial organization, policy processes, international affairs and intergovernmental initiatives have affected the sector. Insightful and authoritative, this volume will be a helpful resource for senior students and scholars in the fields of political science, forestry, public administration, history, geography, and Canadian, environmental, and labour studies. It will also be of value to policy makers who must grapple with the complexity of policy-making in the sector on a day-to-day basis.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 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 it