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Record W4399125278 · doi:10.18280/ijsdp.190523

Women Empowerment as a Mediator Between Environmental Conservation and Climate Intervention

2024· article· en· W4399125278 on OpenAlexvenueno aff
Sania Khan

Bibliographic record

VenueInternational Journal of Sustainable Development and Planning · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicEnergy and Environment Impacts
Canadian institutionsnot available
FundersPrince Sattam bin Abdulaziz University
KeywordsEmpowermentIntervention (counseling)MediatorEnvironmental planningClimate changeEnvironmental resource managementEnvironmental sciencePolitical sciencePsychologyEcologyMedicine

Abstract

fetched live from OpenAlex

The study investigated the influence of environmental conservation on climate intervention and explored how women empowerment mediates between the both.Using survey questionnaire, 246 responses were collected from Saudi women.To understand these associations, Smart PLS-SEM version 4 was employed for data analysis.This study significantly supported all the hypotheses; environmental conservation has a positive significant impact on climate intervention (β = 0.552; p = 0.003).The research verified that women empowerment plays a mediating role, with statistical significance (β = 0.267; p = 0.015), highlighting their crucial function as key drivers in advancing sustainable development.The study's conclusion highlighted the value of women's empowerment as a link between combating climate change and environmental preservation.Saudi women are found to have sufficient knowledge on environment and have mobility in resources, and be good decision-makers.By identifying and leveraging the unique talents of women, policymakers and practitioners may develop more inclusive and effective strategies for decreasing environmental challenges and building climate resilient communities, thereby helping to realize the goals of Saudi Vision 2030.This study contributes to the ongoing discourse regarding the interplay between gender, climate resilience, and environmental sustainability by endorsing all-encompassing approaches that empower women to be agents of change.

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)0.001
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 score0.164
Threshold uncertainty score0.486

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.009
GPT teacher head0.242
Teacher spread0.233 · 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

Citations5
Published2024
Admission routes1
Has abstractyes

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