MétaCan
Menu
Back to cohort
Record W2118988972 · doi:10.3386/w10945

Demographic Changes and International Factor Mobility

2004· article· en· W2118988972 on OpenAlexafffund
John F. Helliwell

Bibliographic record

VenueNational Bureau of Economic Research · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsUniversity of British Columbia
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsDistribution (mathematics)Demographic economicsEconomicsVariety (cybernetics)Geographic mobilityHuman migrationCapital (architecture)Demographic changeEconomic geographyLabor mobilityGeographyDevelopment economicsPopulationLabour economicsDemographySociology

Abstract

fetched live from OpenAlex

This paper reviews the extent and policy implications of linkages between demographic changes and international factor mobility.Evidence is found of significant demographic effects on both migration and the current account, but for different reasons neither increased migration nor international transfers of savings is expected to offer much assistance in digesting the variety of demographic transitions expected over the next fifty years.The paper also examines more briefly the effects of demography on the factor content of international trade, as exemplified by offshore provision of back-office and other services previously provided closer to home.When considering the consequences of using international capital movements and especially migration to mediate international differences in demographic patterns, I broaden the focus from the usual economic variables, such as the size and distribution of incomes and employment, to consider explicit measures of well-being, which have been shown to depend on far more than economic variables.This has implications for a whole range of policies, both domestic and international, that might help deal with national and global demographic transitions.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.009
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0090.000

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 head0.247
GPT teacher head0.508
Teacher spread0.261 · 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

Citations16
Published2004
Admission routes2
Has abstractyes

Explore more

Same venueNational Bureau of Economic ResearchSame topicMigration and Labor DynamicsFrench-language works237,207