Analyzing The Merging Effect of Agro-Production and Formal Training On Women-Empowerment in Rural-Bangladesh

Bangladesh's agricultural sector is crucial to its economy, and women's participation is emphasized for empowerment and increased agro-production. This study uses a household survey of 200 women in four rural Bangladeshi villages to analyze the impact of independent variables (agricultural production, training facility, media connection) on women's empowerment in the agricultural sector (WEIA). Multiple regression analysis shows that agricultural production, training facility, and media connection positively and significantly influence WEIA. The interaction of agricultural production and training facility also has a positive and significant impact. The findings suggest policy implications for sustainable agriculture and women's empowerment.

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Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2024-12-01
DOI
https://doi.org/10.5281/zenodo.15258274
Primary Topic
Machine Learning in Materials Science
Type
article
Field-Weighted Citation Impact
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article

Analyzing The Merging Effect of Agro-Production and Formal Training On Women-Empowerment in Rural-Bangladesh

SHILAP Revista de lepidopterología
Machine Learning in Materials Science
article

Analyzing The Merging Effect of Agro-Production and Formal Training On Women-Empowerment in Rural-Bangladesh

article en

Abstract

Bangladesh's agricultural sector is crucial to its economy, and women's participation is emphasized for empowerment and increased agro-production. This study uses a household survey of 200 women in four rural Bangladeshi villages to analyze the impact of independent variables (agricultural production, training facility, media connection) on women's empowerment in the agricultural sector (WEIA). Multiple regression analysis shows that agricultural production, training facility, and media connection positively and significantly influence WEIA. The interaction of agricultural production and training facility also has a positive and significant impact. The findings suggest policy implications for sustainable agriculture and women's empowerment.

SHILAP Revista de lepidopterología
World Vision (US)
Zero hunger
Openalex Percentile: Top 73%
Machine Learning in Materials Science
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