Punctuating Which Equilibrium? Understanding Thermostatic Policy Dynamics in Pacific Northwest Forestry
Bibliographic record
Abstract
A key theme among seminal contributions to policy studies, including Baumgartner and Jones (1993; 2002), Sabatier and Jenkins-Smith (1993), and Hall (1989; 1993), is that “external perturbations” outside of the policy subsystem, characterized by some type of societal upheaval, are critical for explaining the development of profound and durable policy changes which are otherwise prevented by institutional stability. We argue that these assumptions, while useful for assessing many cases of policy change, do not adequately capture historical patterns of forest policy development in the U.S. Pacific Northwest. Differences in policy development concerning state and federal regulation of private and public forest lands governing the same problem, region, and population challenge much of the prevailing orthodoxy on policy dynamics. To address this puzzle, we revisit and expand existing taxonomies identifying the levels and processes of change that policies undergo. This exercise reveals the existence of a “thermostatic” institutional setting governing policy development on federal lands that was absent in the institutions governing private lands. This thermostatic institutional arrangement contained durable policy objectives that required policy settings to undergo major change in order to maintain the institution's defining characteristics. Policy scientists need to distinguish such “hard institutions” that necessitate paradigmatic changes in policy settings from those that do not permit them.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.009 |
| Scholarly communication | 0.007 | 0.011 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".