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Long‐term gendered consequences of permanent disabilities caused by the 2005 Pakistan earthquake

2011· article· en· W2172188279 on OpenAlexafffund
Humaira Irshad, Zubia Mumtaz, Adrienne Levay

Bibliographic record

VenueDisasters · 2011
Typearticle
Languageen
FieldHealth Professions
TopicDisaster Response and Management
Canadian institutionsUniversity of Alberta
FundersAlberta Innovates - Health Solutions
KeywordsDistrustPoison controlFlirtingSuicide preventionInjury preventionHuman factors and ergonomicsCoping (psychology)PsychologyMedicineSocial psychologyMedical emergencyPsychiatry

Abstract

fetched live from OpenAlex

This study documents the long-term gendered impact of the 2005 Pakistan earthquake on women and men who were rendered paraplegic as a result of spinal cord injuries sustained during the disaster. Coping mechanisms are also mapped. The findings show that three years after the disaster, paraplegic women are socially, emotionally, and financially isolated. The small stipend they receive is a significant source of income, but it has also led to marital distrust, violence, and abuse. In contrast, men receive full social and emotional support. Their key concern is that the government is not providing them with opportunities to be economically productive. Contemporary discourse and post-disaster policies, while acknowledging the importance of incorporating a gender perspective in the immediate post-disaster period, have failed to acknowledge and address the longer-term gendered impact of disasters, in terms of the different types of impact and strategies adopted by women and men.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.002
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.097
GPT teacher head0.376
Teacher spread0.278 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations53
Published2011
Admission routes2
Has abstractyes

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