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Record W3198415349 · doi:10.1215/00703370-9774978

Safer If Connected? Mobile Technology and Intimate Partner Violence

2022· article· en· W3198415349 on OpenAlexafffund
Luca Maria Pesando

Bibliographic record

VenueDemography · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Media and Politics
Canadian institutionsMcGill University
FundersMax-Planck-Institut für demografische ForschungSocial Sciences and Humanities Research Council of CanadaMcGill University
KeywordsMobile phoneSocioeconomic statusDomestic violenceEmpowermentPoison controlBargaining powerBusinessDemographic economicsPsychologySuicide preventionPopulationEconomic growthPolitical scienceEconomicsSociologyDemographyMedicineEnvironmental health

Abstract

fetched live from OpenAlex

Mobile phones are an invaluable economic asset for low-income individuals and an important tool for strengthening social ties. They may also help women overcome physical boundaries, especially those who are separated from support networks and are bound within their husbands' social spheres. Using micro-level data on women and men from recent Demographic and Health Surveys, including new information on mobile phone ownership, this study examines whether women's ownership of mobile phones is associated with their likelihood of having experienced intimate partner violence (IPV) across 10 low- and middle-income countries. Findings show that women's ownership of mobile phones is associated with a 9%-12% decreased likelihood of emotional, physical, and sexual violence over the previous 12 months, even after controlling for characteristics proxying for socioeconomic status, household resources, and local development within the community. Estimates are negative in seven out of the 10 countries and results are robust to the use of nonparametric matching techniques and instrumental variables built through georeferenced ancillary sources. In exploring two potential mechanisms, I show that mobile phone ownership is positively associated with women's decision-making power within the household (decision-making power) and male partners' lower acceptability of IPV (attitudes). Findings speak to scholars and policymakers interested in how technology diffusion relates to dynamics of women's empowerment and global development.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.833
Threshold uncertainty score0.664

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.011
GPT teacher head0.290
Teacher spread0.280 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations34
Published2022
Admission routes2
Has abstractyes

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