Morality, Emotions, and the Ideal Environmentalist: Toward A Conceptual Framework for Understanding Political Polarization
Bibliographic record
Abstract
Americans are politically polarized in their views on environmental protection, and scholars have identified structural and cultural drivers of this polarity. Missing from these theories is a consideration of the emotional dynamics at play in environmentally relevant interactions between liberals and conservatives. Based on analyses of in-depth interviews conducted with 63 politically and socioeconomically diverse residents of four communities in Washington State, we find evidence of important common ground across the political spectrum. Our participants voice support and respect for environmental protection and convey a shared image of an ideal environmentalist: a conscious, caring, and committed individual who seeks to reduce their personal environmental impact. We see political differences arise when our participants evaluate their own relationship with the environment against this ideal environmentalist. Liberals are more likely to align with or admire the ideal environmentalist and conservatives are more likely to challenge or denigrate the ideal. Emotions and competing claims for moral worth, we suggest, play a role in making these political differences polarizing.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.004 | 0.025 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 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".