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Record W1993380980 · doi:10.3828/idpr.2012.16

Cyclone, coastal society and migration: empirical evidence from Bangladesh

2012· article· en· W1993380980 on OpenAlexfundno aff
Bishawjit Mallick, Joachim Vogt

Bibliographic record

VenueInternational Development Planning Review · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change, Adaptation, Migration
Canadian institutionsnot available
FundersKarlsruhe House of Young ScientistsKatholischer Akademischer Ausländer-DienstUniversity of Ottawa
KeywordsCyclone (programming language)Empirical evidenceDevelopment economicsEconomic geographyNatural resource economicsOceanographyPolitical scienceGeographyEconomicsGeologyEngineering

Abstract

fetched live from OpenAlex

In this study the effectiveness of adaptive coping strategies to reduce the damage cost and its consequences for social structural change are examined. Here, migration is considered as a strategic step to cope with the adverse effect of cyclone Aila of 2009 in Bangladesh. A survey of 288 respondents demonstrated that male members of cyclone victims' family were likely to move nearer cities immediately after the end of relief programme. They live in slum environments to accumulate more money for their dependants, but out-migration from the family creates more social problems for their spouse. It introduces changes in local social structure. Income and asset distribution play a vital role in deciding movement. This study depicts a societal cluster of migration correlating with previous disaster data that introduces a new methodological tool for analysing the disaster-migration nexus.

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)0.006
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 score0.033
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.006
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.001

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 head0.280
GPT teacher head0.409
Teacher spread0.130 · 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

Citations102
Published2012
Admission routes1
Has abstractyes

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