Using the Theory of Planned Behaviour to predict farmers' intention to report livestock depredation and kill hyena
Bibliographic record
Abstract
Abstract Understanding and managing conservation conflicts is important for stakeholders (e.g. policymakers and practitioners) trying to minimise negative impacts on people and biodiversity. A key component of Namibia's community‐based natural resource management system, besides enabling communities to derive benefits from wildlife, is the monitoring of wildlife and reporting of negative wildlife impacts on human lives and livelihoods. Farmers across Namibia may legally kill carnivores found attacking their livestock and may receive financial compensation if reported within 24 h. Both interventions are intended to offset costs and build tolerance towards wildlife. Expanding the Theory of Planned Behaviour by incorporating Descriptive Norm, we investigated farmers' Behavioural Intention to (1) legally kill brown Hyena brunnea and spotted Crocuta crocuta hyena when found killing their livestock and (2) report livestock depredation incidents to the relevant authorities in two governance contexts—inside versus outside communal conservancies. We hypothesised famers inside communal conservancies would have lower behavioural intentions to kill hyena and stronger intentions to report livestock depredation compared to farmers outside conservancies. Questionnaire data were collected from 1139 farmers from inside ( n = 945) and outside ( n = 188) communal conservancies. Most respondents reported no intention to kill hyena that killed their cattle, with no significant difference between farmers living inside (89%) and outside (90%) conservancies. Intention to report depredation incidents differed significantly between groups, with 90% of respondents inside conservancies intending to report compared to 78% outside conservancies. Inside conservancies, Attitude was the strongest predictors of farmers' Behavioural Intention to kill hyena and report incidents of livestock depredation. Outside conservancies, intention to kill hyena was most strongly associated with Perceived Behavioural Control, whilst Attitude was the strongest predictor of intention to report. Including Descriptive Norm improved model fit. Our findings highlight how socio‐psychological factors differ between governance contexts and how they subsequently influence farmer's behavioural intentions. Our improved understanding of perceptions underpinning farmers' decision‐making can inform the design of interventions to reduce retaliatory killing and improve reporting of wildlife impacts. Results from this study could also improve the interpretation of national depredation databases and guide more effective mitigation strategies. 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".