Political Common Ground on Preserving Nature: Environmental Motives Across the Political Spectrum
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Environmental issues are becoming increasingly politically polarized, making common ground essential. This research investigated the political common ground of environmental motives—the reasons why nature is worth preserving. Natural language processing of liberals’ and conservatives’ open text responses (Study 1: N = 1,544) identified 12 central motives. Political common ground was shared on the most cited motives: Human survival, moral obligations to future generations, and appreciation for nature’s beauty. Political differences emerged on motives related to climate change risks and religious stewardship. Study 2 ( N = 796) replicated these findings using a validated self-report questionnaire based on participant responses in Study 1. Factor analysis indicated motives belonged to four categories: Responsibility to nature, instrumental benefits, childhood experiences, and religious stewardship. These motives explained substantial variance in environmental attitudes and partially accounted for political differences in attitudes. The studies used mixed methods and direct/conceptual replication to build confidence in key findings and longstanding theoretical frameworks.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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 it