Windmills and Landfills: Framing Controversial Environmental Policies as a Risk to Human Health and Conflict Expansion Strategies
Bibliographic record
Abstract
Conflicts about environmental policies are often focused on the risk to human health posed by a facility or technology. Genetically modified food, oil pipelines, and pesticides are examples of policy issues that have generated tremendous debate related to human health and safety. A key focus of scholarship on such contested policy debates places an emphasis on how these policies are framed, how framing alters the policy process and in turn alters policy outcomes. This research project asks how and why the framing of a policy as a threat to human health influences the policy process and policy outcomes? To answer this question, two case studies of environmental conflicts related to controversial facilities are examined and compared: a waste landfill conflict and a large wind energy conflict. This dissertation seeks to integrate an understanding of the role of risk into theories of public policy by building on the approach to analyzing policy conflicts developed by Sarah Pralle. By using a mix of qualitative, quantitative and process tracing methods in these two cases, this research seeks to understand the role of risk frames in conflict expansion strategies and how such frames are used to include new actors and institutions and thereby alter policy outcomes. The key finding in this study reveals the relationship between the framing of a policy as a threat to human health, the institutional venues in which that policy is contested, and the incentives for strategic venue-shopping these produce. When policy actors are able to successfully frame a facility as a threat to human health, they are able to shift the conflict over that facility to an institutional venue that does not privilege expert understandings of risk. This venue shift opens the opportunity to defeat the facility in a venue more open to non-expert understandings of risk. This finding is not only theoretically important but should serve as warning that institutional venues such as environmental assessment processes that restrict the consideration of risk to expert based assessments will only incentivize opponents to seek out new venues in which to pursue their goals.
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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 | 0.021 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.015 | 0.042 |
| Scholarly communication | 0.013 | 0.016 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.005 | 0.005 |
| 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".