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Record W2609797798 · doi:10.1111/disa.12229

Remittances as aid following major sudden‐onset natural disasters

2017· article· en· W2609797798 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueDisasters · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsGlobal Affairs Canada
Fundersnot available
KeywordsRemittanceNatural disasterFinancial crisisEconomicsBusinessDevelopment economicsGeographyEconomic growthMacroeconomics

Abstract

fetched live from OpenAlex

There is a general assumption, based on macroeconomic studies, that remittances will rise following major sudden-onset natural disasters. This is confirmed by a few assessments involving country-specific research, and usually short-term data. This study, questioning conventional wisdom, reviewed and graphed annual and quarterly remittance flows using International Monetary Fund and World Bank data from 2000-14 for 12 countries that confronted 18 major natural disasters. It found that, regardless of event type, annual remittances rose steadily from 2000-14 except for after the 2008-09 financial crisis. Post disaster, there was a quarterly increase in the majority of cases (confirming previous research) but there was seldom an annual increase in the year of the disaster greater than the average annual increase in 2000-14. It appears that remittance senders rush to provide assistance after a natural disaster, but since their own financial situation has not changed, the immediate increase is compensated by a later decrease.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.458
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.014
GPT teacher head0.325
Teacher spread0.311 · 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