"My cousin bought the phone for me. I never go to mobile shops."
Bibliographic record
Abstract
The intersection of Islam and gender affect technological and social interactions for Muslim women in significant ways and remains an understudied domain for CSCW and related fields. Building on 73 qualitative interviews with low-income women in Punjab, Pakistan, we analyze the complexity of family relationships and the subsequent dynamics of authority around technology uptake and usage by women within non-Western contexts, and, specifically, within the Islamic world. We argue that a Pakistani woman's experience with technology depends on many factors, including gendered roles, generational differences in a family, and wider socio-cultural and religious influences against the backdrop of a culturally conservative and patriarchal society. Our paper highlights the rich family dynamics, including key life events, that transform the roles of both Muslim women and their relatives. Our work is intended to inform scholars, practitioners within development agencies and industry, and other individuals studying technology and development about household dynamics that influence Muslim women's use of technology to encourage them to consider these dynamics during design and implementation processes for technological inclusion.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".