Addressing the Challenges of Adaptation to Climate Change Policy: Integrating Public Administration and Public Policy Studies
Bibliographic record
Abstract
With growing attention on formulating the “right” policies and programs to address climate change, the contribution that policy work will make in fostering adaptive capacity needs to be examined. Policy capacity is crucial to policy formulation and should be at the heart of climate mainstreaming. There are six hypotheses about the nature of climate-based policy work based on a survey conducted of Canadian federal and provincial government employees in the forestry, finance, infrastructure, and transportation sectors. To measure the simultaneous effects on perceived policy capacity, an Ordinary Least Squares regression was conducted. Among the key findings was that the increased demand for climate change science within an organization resulted in a decreased perception of policy capacity. Policy work was largely focused on procedure activities rather than on evaluation. The model found that networking was critically important for perceived policy capacity. Effective policy formulation will involve the participation of others normally not associated with traditional policy work. Evidence-based policy work illustrates that policy success can be achieved by improving the amount and type of information processed in public policy formulation.
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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 | 0.047 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.006 | 0.015 |
| Scholarly communication | 0.020 | 0.019 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".