Social Norms for Illegal Hunting and Patrolling to Prevent It: Formative Data for Intervention Design and Communication Campaigns
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
Community-driven initiatives aimed at curbing wild animal poaching can effectively mitigate species decline, tailor programs to community needs, and align with community members’ preferences. This paper reports on formative data framed within the financial incentives in normative systems (FINS) model. Through in-depth interviews with ethnically Tibetan pastoralists, we find evidence for anti-poaching descriptive and injunctive norms, along with norms endorsing interventions to stop hunting. Our findings indicate that communication regarding wildlife protection is less prevalent within family or friendship groups but more commonly conveyed by governmental and spiritual leaders. The findings suggest anti-poaching efforts could include local community members as well as community leaders and consider existing culturally and spiritually driven attitudes and social norms which are anti-hunting and pro-animal protection.
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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 it