Women’s agency in Egypt: construction and validation of a multidimensional scale in rural Minya
Bibliographic record
Abstract
BACKGROUND: Measurement of women's agency in specific sociocultural conditions, particularly in Middle Eastern settings, has received limited attention, making its usefulness as an outcome or predictor of gender equality unclear. AIMS: This study aimed to construct and validate a multidimensional and context-specific scale of women's agency in rural Minya, Egypt. METHODS: Using data from 608 ever-married women in 2012, confirmatory and exploratory factor analysis were used to construct a scale measuring women's agency in rural Minya. The scale was validated through exploratory structural equation models. RESULTS: The 21-item model consisted of three factors (decision-making, freedom of movement and gender role attitudes), each corresponding to a previously-theorized domain of women's agency. The three factors were positively correlated, supporting women's agency as a multidimensional, context-specific construct. The strongest correlation was between decision-making and freedom of movement (0.410), and then between freedom of movement and gender attitudes (0.307); the weakest correlation was between decision-making and gender attitudes (0.211). Although we hypothesized that each domain would be positively associated with age, only decision-making was significantly and positively associated with women's age. CONCLUSION: Similarities between the items used here and a study at the national level in Egypt suggest these indicators could be used in various Egyptian settings to monitor progress on the United Nations Sustainable Development Goal 5 on empowering women and girls, and to assess the effect of policies and programmes. Future research should build on the findings to identify the best observable indicators of women's agency in Egypt and elsewhere.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".