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Record W2136307323 · doi:10.1177/097152150100800203

Integrating Gender Concerns into Natural Resource Management

2001· article· en· W2136307323 on OpenAlexfundno aff
P. Thamizoli

Bibliographic record

VenueIndian Journal of Gender Studies · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicConservation, Biodiversity, and Resource Management
Canadian institutionsnot available
FundersMultiple Sclerosis Scientific Research Foundation
KeywordsTamilGovernment (linguistics)Equity (law)Participatory rural appraisalNatural resource managementNatural resourceParticipatory developmentCitizen journalismEmpowermentMonitoring and evaluationEconomic growthPublic relationsPolitical scienceSociologyEnvironmental resource managementBusinessAgricultureGeographyEconomics

Abstract

fetched live from OpenAlex

The deep shift after the late 1970s in ways of thinking, seeing and acting led to the quest for small localised narratives, and participatory approaches committed to equity. This paper describes an attempt to integrate a participatory approach and gender concerns in problem anal ysis, planning, implementation, monitoring and evaluation in a project to conserve and manage the Pichavaram mangrove forests in Tamil Nadu. It also deals with the process of enhancing the equitable socioeconomic impacts of the intervention in the coastal villages, sensitising the forest officials, and developing their skills and those of the village community to facilitate women's participation at all levels. In the gender-sensitive micro-plan prepared to address the concerns identified through participatory rural appraisal, both men and women shared responsibilities: meeting government officials, legitimising their tribal identity, constructing and running an elementary school, and restoring and managing the mangroves. This process has enhanced the women's self-confidence, their capacity to save, and their control over income and mobility.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.289
Threshold uncertainty score0.517

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.047
GPT teacher head0.274
Teacher spread0.227 · 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 designObservational
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

Citations6
Published2001
Admission routes1
Has abstractyes

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