Development of a Tool to Measure Women’s Agency in India
Bibliographic record
Abstract
Ensuring and expanding women’s agency is an essential component of efforts to promote the rights and well-being of women. However, inadequate measurement hampers monitoring and research into achieving this goal. In this study, we developed a theory-based measurement tool of women’s agency. We developed a conceptual model of agency through a review of the literature, and then used this model to identify potential indicators of agency. These indicators were asked as part of a population-based household survey that was completed between July and November 2016 by 3042 women in rural Rajasthan, India. We tested the construct validity of the hypothesized measurement model using confirmatory factor analysis. We identified a conceptual model of agency, composed of 23 indicators, which measured the domains Household Decision-Making, Freedom of Movement, Participation in the Community, and Attitudes and Perceptions. This conceptual model fit the study data well (CFI = 0.974, TLI = 0.970, RMSEA = 0.031). Our results have implications for measurement efforts in a number of settings, and our tool can be used to measure women’s agency in rural India.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".