The Shifting Constitution of Space, Gender, and Mobility in a Context of Social and Infrastructural Change: A Case Study of Swat, Pakistan
Bibliographic record
Abstract
Feminist geographers argue that gender and mobility are co-constituted. However, few studies focus on this relationship empirically, and even fewer in the global South. Against this backdrop, this study aims to analyze the ways in which space, gender, and mobility are mutually constituted in Swat Valley, Pakistan, in a shifting historical context of (a) traditional Pukhtun culture involving a syncretic religion, (b) Islamic fundamentalism and the takeover by the Taliban, and (c) post-Taliban modernization in its various forms, including a new market economy and tourist-based infrastructure development. This study temporally maps these particular spatial, gendered, and mobility changes over a period of time (16th century to present), showing that (a) gendered spatiality in traditional Swat evolved in such a way to constitute culturally designated women’s spaces that allowed them to perform their womanhood and practice their mobilities; (b) more recently, Islamic fundamentalist ideologies fundamentally controlled women’s mobilities to erase them from both public space and certain types of private space that had formerly been accessible to women (e.g., shrines); and (c) modernization and infrastructure development created material sites of mobility that provide spaces for middle-class families to perform their modern gender subjectivities.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.016 | 0.013 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".