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Record W3101608015 · doi:10.1111/caje.12474

Migration as a test of the happiness set‐point hypothesis: Evidence from immigration to Canada and the United Kingdom

2020· article· en· W3101608015 on OpenAlexaffvenueabout
John F. Helliwell, Hugh Shiplett, Aneta Bonikowska

Bibliographic record

VenueCanadian Journal of Economics/Revue canadienne d économique · 2020
Typearticle
Languageen
FieldPsychology
TopicPsychological Well-being and Life Satisfaction
Canadian institutionsStatistics CanadaUniversity of British ColumbiaCanadian Institute for Advanced Research
Fundersnot available
KeywordsHappinessImmigrationLife satisfactionTest (biology)Demographic economicsEconomicsSet (abstract data type)KingdomSubjective well-beingPoint (geometry)PersonalitySelection (genetic algorithm)PsychologyPolitical scienceSocial psychologyMathematics

Abstract

fetched live from OpenAlex

Abstract Strong versions of the set‐point hypothesis argue that subjective well‐being measures reflect primarily each individual's own personality and that deviations are temporary. International migration provides an excellent test, since life circumstances and subjective well‐being differ greatly among countries. With or without adjustments for selection effects, the levels and distributions of immigrant life‐satisfaction scores for immigrants to the United Kingdom and Canada from up to 100 source countries mimic those in their destination countries, and even the destination regions within those countries, rather than those in their source countries, showing that subjective life evaluations are substantially driven by life circumstances and respond when those circumstances change.

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)0.013
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 score0.015
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.006
Science and technology studies0.0040.002
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.177
GPT teacher head0.224
Teacher spread0.048 · 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

Citations19
Published2020
Admission routes3
Has abstractyes

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