Post-disaster resettlement, development and change: a case study of the 1990 Manjil earthquake in Iran
Bibliographic record
Abstract
Planned and involuntary resettlement after natural disasters has been a major policy in post-disaster reconstruction in developing countries over the past few decades. Studies show that resettlement can result in significant adverse impacts on the resettled population. Conversely, a well-planned and managed resettlement process can produce positive long-term development outcomes. This article presents the results of a case study undertaken 11 years after the 1990 Manjil earthquake in Iran. During the reconstruction period, a policy of involuntary planned resettlement was pursued extensively. The socioeconomic changes that occurred as a consequence of this policy of involuntary resettlement are analysed. Data were collected via a questionnaire survey that involved a sample of 194 relocated households (grouped into a settlement that later became a town). The paper shows that relocated families face difficult socioeconomic challenges after relocation and regrouping. This is especially true with respect to employment, income, the empowerment of women and lifestyle issues.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".