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Record W4413987753 · doi:10.1080/08941920.2025.2553350

Sacred Natural Sites Conservation in India: Examining Supernatural Institutions Through Ostrom’s Design Principles and Gender

2025· article· en· W4413987753 on OpenAlexaff
Shruti Mokashi, Praneeta Mudaliar

Bibliographic record

VenueSociety & Natural Resources · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicIndian History and Philosophy
Canadian institutionsGeneral Electric (Canada)University of Toronto
FundersCollege of Environmental Science and Forestry, State University of New York
KeywordsNature ConservationNatural (archaeology)Environmental ethicsNatural resourcePolitical scienceSociologyEnvironmental resource managementEnvironmental planningGeographyEcologyArchaeologyEconomicsLawPhilosophy

Abstract

fetched live from OpenAlex

Sacred Natural Sites (SNS), a type of sacred commons managed through supernatural institutions (SIs), may serve as conservation models due to their historical longevity and ecological benefits. Given the persistence of SNS, it is likely that Ostrom’s design principles (DPs) may be represented in SIs for managing SNS, but research on whether SIs promote gender equity is limited. This research examines whether SIs correspond to Ostrom’s DPs and the gender implications of SIs. Through eighty-six semi-structured interviews conducted in villages with SNS in Bhimashankar Wildlife Sanctuary region, India, we find that SIs are aligned with DPs and present a low-cost option for conservation. However, SIs continue upholding patriarchal norms that exclude and disadvantage women from accessing SNS, temples, and decision-making venues. Equity in SNS management must be critically examined in enduring SIs to enhance conservation and policy integration if SNS are to serve as a conservation model.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.837
Threshold uncertainty score0.844

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.124
GPT teacher head0.276
Teacher spread0.152 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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