Technology as the key to women’s empowerment: a scoping review
Bibliographic record
Abstract
BACKGROUND: Information and communications technologies (ICTs) have empowered people to communicate and network at a global scale. However, there is lack of in-depth understanding of the use of ICTs for women's empowerment. This study examines how the concept empowerment is defined, utilized and measured in research studies, the existing evidence on the use of ICTs for women's empowerment and the gaps in knowledge at the global level. METHODS: The authors' conducted a scoping review using the Arksey and O'Malley methodology. The search identified papers from ten databases, including Scopus, Embase, ABI Inform, Soc Index, Sociological Abstracts, Gender Studies, Springer Link, PsychInfo, Science Direct, and Academic Search Complete over the period of 2012-2018. Search criteria included articles that focused on women's empowerment and utilized technologies as interventions. Out of a total of 4481 articles that were initially identified, 51 were included. RESULTS: Technology played a variety of roles in supporting the development of women's capacities and resources. Results revealed the use of ICT interventions in the overarching areas of outreach (e.g., health promotion), education (e.g., health literacy opportunities), lifestyle (e.g., peer coaching and planning), prevention (e.g., screening opportunities), health challenges (e.g., intimate partner violence apps), and perceptions of barriers (i.e., uptake, utilization and ubiquity to ICTs for women). Despite the positive use of technology to support women in their daily lives, there was a lack of consensus regarding the definition and use of the term empowerment. The concept of empowerment was also inconsistently and poorly measured in individual studies making it difficult to determine if it was achieved. CONCLUSION: This scoping review provides a comprehensive review of current and emerging efforts to use ICTs to empower women. The findings suggest a need for collaborative efforts between researchers, program implementers and policy makers as well as the various communities of women to address the persistent gender disparities with respect to ICTs.
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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 | 0.012 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.014 | 0.017 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".