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Record W1648612133 · doi:10.3138/cpp.2015-008

Regulated Health Professions: Outcomes by Place of Birth and Training

2015· article· en· W1648612133 on OpenAlexaffvenueabout
Yaw Owusu, Arthur Sweetman

Bibliographic record

VenueCanadian Public Policy · 2015
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicOccupational and Professional Licensing Regulation
Canadian institutionsMcMaster University
Fundersnot available
KeywordsEarningsPossession (linguistics)Affect (linguistics)Demographic economicsForeign bornWork (physics)Training (meteorology)Place of birthPsychologyLabour economicsBusinessMedicineEconomicsPolitical scienceImmigrationGeographyEnvironmental healthAccountingLawPopulation

Abstract

fetched live from OpenAlex

Do foreign birth and/or the possession of foreign academic credentials affect integration into Canadian regulated health occupations? While there are a few important commonalities across the eight occupations studied, especially that the foreign born, foreign trained are less likely to work in their trained profession, there are a number of differences. Broad-based policies will, therefore, have occupation-specific impacts. Among those actually working in their trained field, place of study/birth earnings gaps are frequently not statistically different from zero and, when non-zero, are negative for some occupations and positive for others. For workers who surmount the regulatory/employment hurdles, there is no evidence of sector-wide systematic earnings penalties to foreign birth/training although such effects may exist in selected occupations.

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)0.008
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 score0.986
Threshold uncertainty score0.102

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.003
Science and technology studies0.0020.002
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0110.001

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 head0.100
GPT teacher head0.293
Teacher spread0.193 · 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

Citations17
Published2015
Admission routes3
Has abstractyes

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