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Record W2090764365 · doi:10.5539/enrr.v2n4p128

Gender Relations in Environmental Entitlements: Case of Coastal Natural Resources in Tanzania

2012· article· en· W2090764365 on OpenAlexvenueno aff
Albinus M. P. Makalle

Bibliographic record

VenueEnvironment and Natural Resources Research · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Education and Sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsEmpowermentTanzaniaNatural resourceParticipatory action researchAction (physics)Participant observationCitizen journalismFocus groupGender relationsNatural (archaeology)SociologyPolitical scienceEnvironmental resource managementEconomic growthSocioeconomicsGeographyGender studiesSocial scienceEconomicsLaw

Abstract

fetched live from OpenAlex

The paper is about a study that rested on the mapping of how men and women gain entitlements (access to, ownership and control) of coastal resources through endowments, referred to herein as environmental entitlements. Environmental entitlements are enhanced by institutional means and mechanisms and the policy dimension of which demand specific forms of action to promote and protect them. The central role played by institutions (regularised patterns of behaviour between men and women in society) in bringing about changes to the environment and society relationships, was the premises of the study. The study explored on how men and women command natural resources that are instrumental to their wellbeing (van Ingen, Kawau, & Wells, 2002). A combination of data collection techniques were used, which included in-depth household interviews, focus group discussions, participant observations, and documentary review to capture the understanding of the relationship between environmental entitlements and gender roles. Various alternative conceptualisations of gender-environment relations, which can roughly be thought of as translations of the findings into the environment domain, were also used. As an action research, it highlighted a number of empowerment issues for participatory implementation with the focus on women. This is in recognition that there is undervaluation of both environmental resources and of women’s labour in managing and conserving these.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.021
GPT teacher head0.310
Teacher spread0.290 · 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.

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

Citations5
Published2012
Admission routes1
Has abstractyes

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