MétaCan
Menu
Back to cohort
Record W2055942910 · doi:10.1111/imre.12094

Do Pathways Matter? Linking Early Immigrant Employment Sequences and Later Economic Outcomes: Evidence from Canada

2014· article· en· W2055942910 on OpenAlexafffundabout
Sylvia Fuller

Bibliographic record

VenueInternational Migration Review · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsUniversity of British Columbia
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsImmigrationTypologyOddsDemographic economicsSettlement (finance)Opportunity structuresLabour economicsLife course approachEconomicsSociologyPolitical sciencePsychologyPoliticsSocial psychologyLogistic regression

Abstract

fetched live from OpenAlex

Employment mobility is a critical feature of immigrants’ settlement experiences and longer-term life chances. While current research typically treats mobility as a singular outcome, becoming established in a new labor market is a complex process that can entail multiple transitions in and out of employment and between different types of jobs over time. This article advances understanding of the process of immigrant labor market incorporation by engaging with its potentially multidimensional, cumulative, and path-dependent aspects. Using data from the Longitudinal Survey of Immigrants to Canada, I test the impact of an empirically derived typology of month-by-month immigrant employment trajectories on the odds of occupational degradation and on weekly wages. I find that the pathways immigrants take through the labor market in their first four years constitute a distinct and important mechanism shaping later employment outcomes.

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)0.004
metaresearch head score (Gemma)0.009
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 score0.016
Threshold uncertainty score0.113

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.009
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0020.002
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 head0.028
GPT teacher head0.301
Teacher spread0.273 · 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

Citations50
Published2014
Admission routes3
Has abstractyes

Explore more

Same venueInternational Migration ReviewSame topicMigration and Labor DynamicsFrench-language works237,207