Social Repercussion of Translocating a Jaguar in Brazil
Bibliographic record
Abstract
The translocation of “problem-animals” is a common non-lethal strategy to deal with human-wildlife conflict. While processes of wildlife translocation have been widely documented, little is known about the social repercussions that take place once the capture and the return of a problem-animal to its natural habitat fail and it has to be permanently placed in captivity. We investigated how the public, an important stakeholder in wildlife conservation, perceived the translocation of a female jaguar to a wildlife captivity center. The objectives were to (1) assess the public's perceptions (e.g., attitudes, emotions, awareness) toward the jaguar and its translocation process, and (2) how these psychological constructs are related. We used the social media profiles of the three institutions involved in the process (one responsible for the jaguar rescues, one that supported its recovery, and the one responsible for the jaguar's final destination) and analyzed the comments left by their followers on posts related to the jaguar and the translocation itself during 25 days. A total of 287 comments were analyzed through coding, a categorizing strategy of qualitative analysis; 33 codes were identified. Results showed high admiration for the work done, positive attitudes and emotions, and concern toward the animal. Lack of awareness about the translocation process was high, with comments of curiosity toward the situation being one of the most commonly found. To a lesser extent, people felt sad for the jaguar not being able to return to the wild and criticized the need for translocation. Admiration for the work had a strong relation with gratitude and broader positive perceptions toward the jaguar's story. Criticism related to concern, which was also related to a need for more information and curiosity. Our findings suggest that the public who engaged with those institutions through their Instagram accounts were grateful for seeing the jaguar safe, but were not aware of the complexity of the operation nor about the nature of the conflict with farmers. The public can either reinforce a particular action or jeopardize an entire operation, depending on their perceptions of the matter. In the case of this jaguar, the public held a positive view; however, we acknowledge the limitations of our sample and recommend further analyses of social repercussions among people who are not followers of these organizations. Furthermore, we recommend engaging other stakeholders to fully understand the human dimensions of translocating this jaguar. Finally, for social acceptance, we highlight the importance of transparency and reliability of the organizations operating the translocation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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 source (direct Gemma or distilled Codex), 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".