Awareness and Attitudes towards Vultures in Communities around Manyelanong and Tswapong Hills, Botswana
Bibliographic record
Abstract
Several vulture species are classified as endangered due to their massive global decline in populations. Humans and other species in the ecosystem may suffer because of this decline. Identification of vulture conservation threats, and creation of sustainable wildlife conservation depends on understanding the attitudes and views of local communities. Research on threats, attitudes, and views of local communities towards vulture conservation in Botswana is limited. The current study yields key insights about the perceptions and knowledge of local communities towards vultures in the Manyelanong and Tswapong hills, Botswana which are crucial foraging and breeding habitats for cape vultures Gyps coprotheres. A questionnaire survey was employed, comprising both open-ended and closed-ended questions about respondents’ perceptions of vultures, their knowledge of them, and how frequently they had seen them in their neighbourhoods. The questionnaire was implemented on 120 randomly selected households near the breeding grounds of vultures. Both qualitative and quantitative techniques were used to analyse the data. Some socioeconomic factors, including education level, age, occupation, residence, and favourable attitude towards vultures, showed a significant association. The physical and behavioural traits of the species had an impact on how the locals felt about vultures. Age, education, and participation level of respondents had an impact on their attitudes towards conservation. The ecological significance of vulture species is recognised by communities, who are concerned about their population declines. Therefore, comprehensive awareness-raising campaigns should be encouraged to protect vulture species.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".