Large-scale rollout of extension training in Bangladesh: Challenges and opportunities for gender-inclusive participation

dc.creatorMedendorp, J.W.
dc.creatorReeves, N.P.
dc.creatorSal y Rosas Celi, V.G.
dc.creatorHarun-Ar-Rashid
dc.creatorKrupnik, T.J.
dc.creatorLutomia, A.N.
dc.creatorPittendrigh, B.R.
dc.creatorBello-Bravo, J.
dc.date2022-07-22T00:25:14Z
dc.date2022-07-22T00:25:14Z
dc.date2022
dc.date.accessioned2023-07-17T20:09:21Z
dc.date.available2023-07-17T20:09:21Z
dc.identifierhttps://hdl.handle.net/10883/22130
dc.identifier10.1371/journal.pone.0270662
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/7513892
dc.descriptionDespite the recognized importance of women’s participation in agricultural extension services, research continues to show inequalities in women’s participation. Emerging capacities for conducting large-scale extension training using information and communication technologies (ICTs) now afford opportunities for generating the rich datasets needed to analyze situational factors that affect women’s participation. Data was recorded from 1,070 video-based agricultural extension training events (131,073 farmers) in four Administrative Divisions of Bangladesh (Rangpur, Dhaka, Khulna, and Rajshahi). The study analyzed the effect of gender of the trainer, time of the day, day of the week, month of the year, Bangladesh Administrative Division, and venue type on (1) the expected number of extension event attendees and (2) the odds of females attending the event conditioned on the total number of attendees. The study revealed strong gender specific training preferences. Several factors that increased total participation, decreased female attendance (e.g., male-led training event held after 3:30 pm in Rangpur). These findings highlight the dilemma faced by extension trainers seeking to maximize attendance at training events while avoiding exacerbating gender inequalities. The study concludes with a discussion of ways to mitigate gender exclusion in extension training by extending data collection processes, incorporating machine learning to understand gender preferences, and applying optimization theory to increase total participation while concurrently improving gender inclusivity.
dc.languageEnglish
dc.publisherPublic Library of Science
dc.relationhttps://figshare.com/articles/dataset/Minimal_data_set_/20275794
dc.relationNutrition, health & food security
dc.relationTransforming Agrifood Systems in South Asia
dc.relationResilient Agrifood Systems
dc.relationMichigan State University
dc.relationPurdue University
dc.relationBorlaug Higher Education for Agricultural Research and Development Program
dc.relationBill & Melinda Gates Foundation
dc.relationUnited States Agency for International Development
dc.relationhttps://hdl.handle.net/10568/127575
dc.rightsCIMMYT manages Intellectual Assets as International Public Goods. The user is free to download, print, store and share this work. In case you want to translate or create any other derivative work and share or distribute such translation/derivative work, please contact CIMMYT-Knowledge-Center@cgiar.org indicating the work you want to use and the kind of use you intend; CIMMYT will contact you with the suitable license for that purpose
dc.rightsOpen Access
dc.source7 July
dc.source17
dc.source1932-6203
dc.sourcePLoS ONE
dc.sourcee0270662
dc.subjectAGRICULTURAL SCIENCES AND BIOTECHNOLOGY
dc.subjectSpecific Training Preferences
dc.subjectADULTS
dc.subjectAGRICULTURAL WORKERS
dc.subjectFEMALES
dc.subjectGENDER
dc.subjectHUMANS
dc.subjectMACHINE LEARNING
dc.titleLarge-scale rollout of extension training in Bangladesh: Challenges and opportunities for gender-inclusive participation
dc.typeArticle
dc.typePublished Version
dc.coverageBangladesh
dc.coverageUSA


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