{"id":"W3192329351","doi":"10.1111/josi.12470","title":"The representation of ethnic economies in industry clusters and the earnings differences of ethnic members from others: A case of Chinese in Canada","year":2021,"lang":"en","type":"article","venue":"Journal of Social Issues","topic":"Migration, Ethnicity, and Economy","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Ethnic group; Earnings; Context (archaeology); Cluster (spacecraft); Ethnic chinese; Representation (politics); Business; China; Economy; Immigration; Demographic economics; Political science; Economics; Geography; Accounting","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001133252,0.00006123668,0.0003527173,0.00004619728,0.0001140048,0.0000186183,0.0001435879,0.00009689623,0.00009446081],"category_scores_gemma":[0.0006365872,0.00004026975,0.00006811694,0.0002970126,0.0004497224,0.0001895782,0.00002698891,0.0002754132,4.999718e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001101145,"about_ca_system_score_gemma":0.0006396843,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9447377,"about_ca_topic_score_gemma":0.995519,"domain_scores_codex":[0.9984832,0.0005952575,0.0005803878,0.00007294906,0.0001652773,0.0001028942],"domain_scores_gemma":[0.99796,0.001042887,0.000782572,0.00005911837,0.0001259429,0.00002951412],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0000913311,0.00002122174,0.4917537,0.00001520459,0.00007123162,0.00001503309,0.5050304,0.0001322906,0.00005395832,0.0002718564,0.00009855221,0.00244527],"study_design_scores_gemma":[0.0006038597,0.00001364133,0.5303104,0.00004329468,0.00001755098,0.000002678622,0.4654514,0.00006690474,0.0001547261,0.003243599,0.00004792829,0.00004401362],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.99338,0.002787805,7.766246e-7,0.003121198,0.0001233114,0.00007355745,0.000005352743,6.751739e-7,0.0005073043],"genre_scores_gemma":[0.997772,0.001912014,0.00001754561,0.00003274217,0.0001239859,0.000001654938,4.143159e-7,0.000003046483,0.0001366207],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05078128,"threshold_uncertainty_score":0.1657021,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03520094102150064,"score_gpt":0.3400029245796084,"score_spread":0.3048019835581078,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}