“Find a Place Where You Can Be a Part of the Change”: A Thematic Analysis of the Conditions that Influence Direct, Collective Pro-Environmental Activism
Bibliographic record
Abstract
The harmful impacts of climate change are becoming increasingly apparent across many aspects of society, and pro-environmental collective activism may help slow its progression. While previous research underscores several factors that shape participation in pro-environmental collective activism, much of this research is informed by quantitative data. This study used qualitative methods to investigate the conditions that shape participation in collective pro-environmental activism. This study drew on four in-depth interviews with climate activists recently engaged in direct action. Data were analyzed using reflexive thematic analysis. Three themes are presented: (a) Tangible and local instances of environmental and social injustices encourage people to act on existing environmental and political values; (b) Activists are motivated to participate in collective activism by a need to belong; (c) A sense of hopeful group efficacy counteracts negative affect about the climate crisis. These findings demonstrate the interactive nature of the conditions that support proenvironmental activism
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How this classification was reachedexpand
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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".