Geographic bias in the media reporting of aquatic versus terrestrial human predator conflicts and its conservation implications
Bibliographic record
Abstract
Interactions or conflicts between humans and large predators occur globally, but an understanding of their spatial occurrence and associated media reporting remains limited. Media reach is now global and rapid, particularly through western news outlets and amplified by social networks. This has consequences for how the public perceive human-predator conflicts and in turn how this impacts species' conservation and management. To address this point, a literature search was undertaken to synthesize global records of predator-human conflicts followed be an assessment of media reporting of conflicts, for both aquatic (sharks) and terrestrial (lion, tiger, leopard, cougar, puma, bear spp.) species. We show that predator-human conflicts involving terrestrial mammals occur predominantly in developing'' nations (>90%) while aquatic predator-human conflicts occur (65%) and are principally reported from developed nations. Moreover, media reporting of sharks is dominated by attacks on humans and sensationalized documentation of incidences compared to those involving terrestrial species. As a result, high media coverage of shark-human conflicts may lead humans to overestimate the risk of being attacked. We recommend increased communication between stakeholders to establish ground rules for media reporting of shark-human conflicts, better informed reporting of attacks, further research undertaken to understand the public's perception of media reporting of conflicts and continued investment in communication, education, and public awareness programs. Through these actions it will be possible to rebalance the public perception of sharks to promote understanding and value of their ecological role and to minimize human-shark incidents.
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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 | 0.001 | 0.001 |
| 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".