Empowering Women in Agriculture: Exploring Their Role and Decision Making Impact – A Study in Manipur, India
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: Manipur, a North-Eastern State of India where about 49.81 per cent of total population is women [1] and they contribute about 51.46 per cent of total working force. The state, which is relatively backward in agricultural development paradigm, has a glorious past regarding women’s ‘movement’ for the state’s cause. Now, it is to be understood properly their role and participation in farm economy for revamping the agrarian situation in the state by exploring the farm women’s role. Methods: The study was conducted by collecting both secondary as well as primary information from sample respondents equally distributed over two valley districts (namely, Thoubal and Imphal East) of Manipur. In all the phases of selection (of sub-division, block, village etc.) the method of probability proportional sampling was employed. Standard econometric methods and statistical packages were applied to elucidate the core objective(s) of the study. Results: The status of participation of farm women in decision making process has been judged with the help of Participatory Index (P.I) and Decision Making Index (DMI). Farm women, in general, participates prominently in socio-cultural matters (DMI = 0.86-0.93) and miscellaneous matters (DMI = 0.83-0.96), moderately in family’s financial/economic matters (DMI = 0.62-0.89) but rather poorly (DMI = 0.43-0.56) in farming matters. More specifically, they are relatively less consulted or are given less importance on matters like consultation with officials (private or government), purchase of household furniture, purchase of improved implements/machineries, selection of crop variety, input management in crop cultivation etc.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it