Factors influencing women’s participation in disaster recovery after the 2005 earthquake in Kashmir, Pakistan
Bibliographic record
Abstract
This study aimed to examine factors that influenced the participation of women in the disaster recovery process after October, 2005 earthquake in the Union Council Langarpura, Azad Kashmir state of Pakistan. To achieve this aim, two focus group discussions, thirty-four (34) semi-structured interviews and participant observations were conducted. The results revealed that women’s participation was influenced by two key factors: the role of social capital and the Kashmir earthquake itself. Three forms of social capital including bonding, bridging and linking social capital encouraged women in Langarpura to participate in the recovery. The Kashmir earthquake influenced women’s participation in disaster recovery due to the death of the men heads of the family and the outmigration of men that compelled women to start working by participating in various recovery projects. The influx of several government and nongovernmental organisations (NGOs) as well as aid organisations after the Kashmir earthquake also encouraged women’s participation in disaster recovery. The findings of this study show that the Kashmir earthquake opened a window of opportunity to change the status of the women of Langarpura and their stereotypical roles in society and go out and take an active part in the recovery of their families and the community at large.
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 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".