The Gender Digital Divide in Rural Pakistan: How Wide is it and How to Bridge it?
Bibliographic record
Abstract
While Pakistan\\xe2\\x80\\x99s National Information Technology (IT) Policy aims at harnessing the potential of information and communication technologies (ICTs) for development, especially in the underserved rural areas, it ignores the role of existing gender inequalities on the possible benefits of ICTs. We have investigated aspects of the \\xe2\\x80\\x98gender digital divide\\xe2\\x80\\x99 in rural areas of Pakistan in order to enable an evidence-based gender-sensitive revision of the policy as well as ICT-related interventions from which both females and males gain. The study took place in four of the most marginalized rural districts of the country where this divide is likely to be most pronounced. We found mobile phones to be the ICT that is most commonly available in rural Pakistan. Radios and TV sets are the second most widespread technologies in marginalised rural areas. However, mobile sets at hand are largely owned by women\\xe2\\x80\\x99s husbands, fathers and brothers, whose permission to make calls is required by a large share of all female respondents. I, therefore, argue that availability and gendered use of ICTs are two different things altogether. Social norms related to women and girls\\xe2\\x80\\x99 access to education as well as regulating their mobility prevent them from using ICTs. These norms have to be taken into account in policies and interventions to ensure women and girls\\xe2\\x80\\x99 access to and beneficial use of ICTs.
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How this classification was reachedexpand
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 | 0.000 | 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 | 0.001 | 0.001 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".