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Record W2795619674

Reversal of Fortunes or Continued Success? Cohort Differences in Education and Earnings of Childhood Immigrants

2011· article· en· W2795619674 on OpenAlexaboutno aff
Feng Hou, Aneta Bonikowska

Bibliographic record

VenueAnalytical Studies Branch Research Paper Series · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsImmigrationEarningsCohortSocioeconomic statusEducational attainmentDemographyNative-BornDemographic economicsCohort effectCohort studyPsychologyMedicinePolitical scienceEconomicsPopulationSociologyEconomic growth
DOInot available

Abstract

fetched live from OpenAlex

Current knowledge about the favourable socioeconomic attainment (in education and earnings) among children of immigrants is based on the experiences of those individuals whose immigrant parents came to Canada before the 1970s. Since then, successive cohorts of adult immigrants have experienced deteriorating entry earnings. This has raised questions about whether the outcomes of their children have changed over time. This study shows that successive cohorts of childhood immigrants who arrived in Canada at age 12 or younger during the 1960s, 1970s, and 1980s had increasingly higher educational attainment (as measured by the share with university degrees) than their Canadian-born peers by age 25 to 34. Conditional on education and other background characteristics, male childhood immigrants who arrived in the 1960s earned less than the Canadian-born comparison group, but the two subsequent cohorts had similar earnings as the comparison group. Female childhood immigrants earned as much as the Canadian-born comparison group, except for the 1980s cohort, which earned more.

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)0.004
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 score0.122
Threshold uncertainty score0.243

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.086
GPT teacher head0.391
Teacher spread0.305 · 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

Citations3
Published2011
Admission routes1
Has abstractyes

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Same venueAnalytical Studies Branch Research Paper SeriesSame topicMigration and Labor DynamicsFrench-language works237,207