Fostering Coexistence: Insights for the Future of Tiger Conservation in India
Bibliographic record
Abstract
The conservation of keystone species like the Bengal Tiger in India is crucial amidst global climate change and biodiversity loss.While Project Tiger has achieved successes, 1 challenges persist where tiger populations decline.This paper examines human-wildlife coexistence through case studies from India and Nepal, emphasizing indigenous communities' relationships with tigers and lions.The Mishmi people of Arunachal Pradesh exemplify deep kinship with Bengal Tigers, stressing the integration of place-based perceptions and indigenous knowledge in conservation.Similarly, Tharu people in Nepal's Chitwan National Park exhibit fine-scale spatial and temporal coexistence with tigers, supported by institutional backing for sustainable prey numbers and reduced exploitation.In Gujarat's Gir Forest, Maldhari people coexist with Asiatic lions, using adaptive measures like nighttime livestock corralling and mixed grazing herds to mitigate lion predation, and relies on government-given grazing rights and economic compensation in the event of cattle predation, highlighting the need for socioeconomic support and institutional frameworks.Although focused on lions, this example is relevant to tiger conservation efforts, as both species are big cats with similar ecological Project Tiger, launched in 1973, is India's government-led initiative aimed at conserving the Bengal Tiger 1 population by establishing protected reserves and combatting threats like poaching and habitat loss.behaviors, providing valuable insights into human-wildlife coexistence strategies.Besides, addressing historical injustices, such as indigenous community displacement for conservation, is crucial.Trust-building and involving local communities in co-management are essential for cooperation between Adivasi and wildlife authorities.By respecting indigenous knowledge, providing socio-economic support, and involving communities in conservation, this paper advocates a holistic approach based on sustainable human-wildlife coexistence for tiger conservation in India.Fostering Coexistence: Insights for the Future of Tiger Conservation in India
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.030 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".