Nature, Causes, and Impact of Human–Wildlife Interactions on Women and Children Across Cultures
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Despite the growing human–wildlife interactions (HWIs) globally, little attention has been paid to their effects on women and children, who often bear the brunt of loss of property and livelihoods. A systematic scoping review of four databases was undertaken to map and synthesize English-language evidence on the nature, causes, and impact of human–wildlife interactions on women and children across cultures. The 42 studies retained reveal that the proximity of human habitation to forest areas; expansion, deforestation, and encroachment of animal space; humans’ dependence on forest resources for livelihood; displacement of carnivores; and animals coming into the human space in search for food are the predominant causes of HWIs. Various types of HWIs and widely varying frequencies and durations of HWIs were reported. Individual and collective aspects of physical, psychological, economic, social, and environmental impacts on women and children were identified. The themes extracted were gendered roles, multi-factor vulnerabilities of women, religious beliefs, low participation of women in decision-making, social superstition against tiger widows, and perceptions of coexistence. Attention to perceptions of HWIs in different cultures and societies was limited, with notable gaps in the coverage of women and children and important geographic areas. These findings stress the need to bridge the geographical and cultural gap through multi-disciplinary actions on the determinants and effects of HWIs on women and children.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it