Women’s economic empowerment: A global pathway to gender equality?
Bibliographic record
Abstract
Abstract Globally, gender equality is the next frontier for social transformation, and women’s economic empowerment is promoted as the pathway to achieve this goal, particularly in countries of the Global South. Women’s economic empowerment is broadly defined as women’s capacity to contribute to, and benefit from, economic activities on terms that recognise the value of their contributions. Advocates for women’s economic empowerment state that it has the potential to be a safeguard against poverty and precarity by enhancing women’s wellbeing. Using a critical-feminist lens, we explore the benefits and risks of the global trend towards women’s economic empowerment. After providing an overview of the evolution of the concept of empowerment, we review the benefits of women’s economic empowerment: economic growth, improved rates of tertiary education and market participation for women, and growth of women’s autonomy. We then examine the risks of the global focus on women’s economic empowerment, which we distil into three key areas: (a) women seen as a country’s ‘natural resource’, used as instruments for economic prosperity and reproduction without considering their wellbeing; (b) a focus on women’s market participation without adequately factoring in current labour market realities; and (c) pushing the women’s economic empowerment agenda forward without fully considering the scope of unpaid reproductive work undertaken by women. We conclude with an analysis of how UN Women (2024) is shifting the agenda by providing a holistic framework for thinking about women’s economic empowerment. We suggest that there is room for cautious optimism if this framework is widely adopted.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.020 |
| Scholarly communication | 0.010 | 0.014 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".