Private and civic actions as distinct types of individual engagement for transforming the exotic pet trade
Bibliographic record
Abstract
Abstract In the pathway toward environmental sustainability, it is important that we understand how individuals can make a difference through diverse types of engagement. Theories suggest that transformative change toward a sustainable future requires individuals to engage in not only private actions (e.g. household energy saving, recycling) but also social‐signalling and system‐changing civic actions (e.g. opinion sharing, voting, petition signing and protesting). Yet, past research on pro‐environmental behaviour has primarily focused on private actions, while overlooking individual contributions to facilitating widespread change through civic actions. We use the exotic pet trade as a focal case to understand how individuals may act to promote environmental sustainability through different patterns of engagement and what factors might explain these distinct patters of action. Results from an online survey about behavioural intentions in the United States ( n = 527) revealed three types of individual action that could transform the exotic pet trade. Private actions clustered separately from civic actions. Within the category of civic actions, a distinction emerged between lower social‐commitment actions and higher social‐commitment actions, based on the perceived level of social engagement and personal efforts involved. We also found that each type of action was associated with unique factors, highlighting the importance of attitudes, perceived social norms, and relational values for variously promoting individual engagement among the U.S. public. Our findings suggest that these distinct types of action should be treated differently when designing future wildlife conservation campaigns and behaviour change interventions. Read the free Plain Language Summary for this article on the Journal blog.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".