Local Climate Action Planning toward Larger Impact: Enhancing a Park System's Contributions by Examining Regional Efforts
Bibliographic record
Abstract
Abstract Regional park systems hold a vital role in the health and well-being of the social-ecological systems within and surrounding them. One role these park systems inherently provide is assistance toward climate change adaptations and mitigations. This article discusses a network of climate action plans (CAPs) in southeastern Michigan, including those in bordering Ohio and Canada, and utilizes a qualitative content analysis to categorize what climate actions are being prioritized throughout the region. Using an integrated recreation amenities framework from traditional park planning research, the analysis includes examination of the content, temporal and spatial scales, and entities responsible for implementation of actions in 10 CAPs in the region. Within this framing, opportunities for parks to complement and extend regional priorities are illuminated and discussed in park-relevant language. This analysis identifies a basic plan framework common across the 10 CAPs from entities in the region: a main focus on managerial, internal actions on a short implementation time frame. Content areas and foci for a park system to capitalize on are also defined, with three prominent themes discussed, including scaled natural resource foci, centering social and community needs, and creating integrated multi-emphasis actions that serve extensive roles. Findings presented here will help inform specific contributions for a metropark system to consider as it creates a regionally appropriate yet distinctive CAP. These findings are not exclusive to southeastern Michigan but could be used to inform regional park systems around the country in how to pursue climate action.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| 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".