Canadian forestry policy-making: failure and resistance or evolution in turbulent times?
Bibliographic record
Abstract
SEPTEMBRE/OCTOBRE 2007, VOL. 83, No 5 — THE FORESTRY CHRONICLE long waves of growth and pressures for perpetual change (Jessop 2002). Economically, the impacts of globalization on the Canadian forest sector are well known (see Hayter and Holmes 2001). However, there has been far less commentary on the relationship between globalization and forest policy-making. The complexity and rapidity of change in the interconnectedness between different policy actors has given rise to increasingly unpredictable change and a growing turbulence in the forest sector (Terreberry 1968). One notable exception, by Kennedy et al. (1998), discusses the transition from a “machine” to an “organic” model of public land management roles and core beliefs. They argue that forestry perspectives radically changed from viewing the sector as composed of simple, independent systems to one that is composed of complex, non-linear, self-organizing, highly integrated systems. Furthermore, there has been a declining and changing role of government agencies (through the reduction of staff and resources) to carry their policies and programs. This, in part, has led to governments playing less of a coordinating and more of a collaboration role with a wide array of policy actors. We present these two views as lenses to examine forest policy-making in Canada. This special issue of The Forestry Chronicle brings together ten articles from authors from diverse backgrounds and representing different aspects of Canada’s forest policy community. These articles provide a sample of the interaction of actors, issues and ideas, and institutions. It is our intention to contribute to the growing forestry policy research literature. The articles examine the policy process at different scales, from the local level (woodlot, watershed) to the international. The content and nature of objectives of each paper may be quite different, but each develops policy options informed by social science and biological research and in some cases consultation with experts and stakeholders. Within these scales, different aspects of policy development and implementation are introduced, examined, and discussed. The first paper, Has the time come to rethink Canada’s Crown forest tenure systems? by David Haley and Harry Nelson critically examines Canada’s forestry tenure system. The authors address two important questions: has the time come to rethink the forest tenure system; and, if so, what directions might these reforms take? They describe the desirCanadian forestry policy-making: failure and resistance or evolution in turbulent times?
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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 | 0.008 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.011 |
| Science and technology studies | 0.040 | 0.024 |
| Scholarly communication | 0.027 | 0.006 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 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".