Frog and reptile conservation through the lens of South Africa’s nature-based cultural practices
Bibliographic record
Abstract
Ethnoherpetology improves our understanding of the conservation implications of nature-based cultural practices through investigations of the influence of traditional culture on frog and reptile species (herptiles). Improved understanding of the implications of human activities on these taxa is especially important as herptiles are experiencing global population declines. Furthermore, improved understanding of nature-based cultural practices can better inform conservation planning that includes cultural practices as defined by South African legislation. The herptile-based cultural practices recorded from a sample of 275 online questionnaire respondents and 68 publications show some cultural practices to compel or inspire protection of herptiles. Conversely, other practices were found to pose a conservation risk as they either involve killing herptile species or they perpetuate negative perceptions towards them. Leveraging protective cultural practices as a conservation tool and mitigating culture-motivated threats requires integrating cultural aspects into modern law. Such an integrative approach is possible under South African legislation’s provisions for socially inclusive conservation planning and recognition of customary law. Integrative conservation approaches are also in line with international policy such as the Kunming-Montreal global biodiversity framework. In addition to an inventory of herptile-based cultural practices, the study also assesses their feasibility as conservation tools. Furthermore, this study highlights a need for quantification of their conservation implications (both positive and negative) and aligning protective traditional cultural practices with modern means of law enforcement.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 0.006 |
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".