Exploring the Disparities in Agricultural Information Networks: Insights from Tribal and Coastal Farm Women of Odisha in India
محل انتشار: مجله علوم و فناوری کشاورزی، دوره: 28، شماره: 1
سال انتشار: 1405
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 3
فایل این مقاله در 18 صفحه با فرمت PDF قابل دریافت می باشد
- صدور گواهی نمایه سازی
- من نویسنده این مقاله هستم
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
JR_JASTMO-28-1_004
تاریخ نمایه سازی: 29 دی 1404
چکیده مقاله:
This study seeks to examine and assess the differences between the social networks of respondents living in tribal areas and in coastal areas. ۲۴۰ respondents from Ganjam and Rayagada, and Odisha were sampled using multiple steps. To map farmers' communication pattern, Social Network Analysis (SNA) was used. Respondents from both areas consider the most educated person in family and village and Self-Help Group (SHG) as their primary source of information, but respondents from coastal area were much smart in networking with other information sources as well, like using TV, training, demonstration, field days, other farmers, agriculture department, input dealers etc. Women farmers were less likely to receive information when betweenness centrality was used in targeting, suggesting there were important gender differences: In tribal area, men are likely to talk to the cosmopolite information sources and respondents are generally engaged in the farm activities more, whereas in coastal area, respondents are actively involved in both farm activities as well as gathering information from different sources.
کلیدواژه ها:
نویسندگان
Shilpa Bahubalendra
Department of Agricultural Extension Education, College of Agriculture, Odisha University of Agriculture and Technology (OUAT), Bhubaneswar, Odisha, India.
Bishnupriya Mishra
Department of Agricultural Extension Education, College of Agriculture, Odisha University of Agriculture and Technology (OUAT), Bhubaneswar, Odisha, India.
مراجع و منابع این مقاله:
لیست زیر مراجع و منابع استفاده شده در این مقاله را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود مقاله لینک شده اند :