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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 OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.687
Threshold uncertainty score0.915

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.100
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