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Record W2127850388 · doi:10.1186/s40176-014-0026-3

Do climate variations explain bilateral migration? A gravity model analysis

2015· article· en· W2127850388 on OpenAlexaff
Andreas Backhaus, Inmaculada Martínez‐Zarzoso, Chris Muris

Bibliographic record

VenueIZA Journal of Migration · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change, Adaptation, Migration
Canadian institutionsSimon Fraser University
FundersBundesministerium für Bildung und Forschung
KeywordsPrecipitationPanel dataEconomicsGravity model of tradeClimate changeInternal migrationEconometricsClimatologyEnvironmental scienceEconomic geographyDemographic economicsGeographyGeologyDeveloping countryMeteorologyInternational economics

Abstract

fetched live from OpenAlex

Abstract This paper investigates to what extent international migration can be explained by climatic variations. A gravity model of migration augmented with average temperature and precipitation in the country of origin is estimated using a panel data set of 142 sending countries for the period 1995 to 2006. We find two primary results. First, temperature is positively correlated with migration. Second, stronger changes in precipitation are also associated with aligned, but small changes in migration. Both effects are robust to various model modifications. Furthermore, we present initial explorations into the channels relating climate changes with migration via agriculture and internal conflict. JEL Codes F22, Q54

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)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.070

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.150
GPT teacher head0.360
Teacher spread0.210 · 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 designSimulation or modeling
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

Citations111
Published2015
Admission routes1
Has abstractyes

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