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

  • John William Medendorp
  • , N. Peter Reeves
  • , Victor Giancarlo Sal y Rosas Celi
  • , Md Harun-Ar-Rashid
  • , Timothy J. Krupnik
  • , Anne N. Lutomia
  • , Barry Pittendrigh
  • , Julia Bello-Bravo
  • Purdue University
  • Sumaq Life LLC
  • Agricultural Advisory Society (AAS)
  • International Maize and Wheat Improvement Center
  • Michigan State University
  • Purdue University

Research output: Contribution to journalArticlepeer-review

22 Scopus citations

Abstract

Despite 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.

Original languageEnglish
Article numbere0270662
JournalPLoS ONE
Volume17
Issue number7 July
DOIs
StatePublished - Jul 2022

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