{"id":"W7095974012","doi":"","title":"HOW DO GENDER AND COUNTRY OF BIRTH AFFECT LABOUR MARKET OUTCOMES FOR IMMIGRANTS? By","year":2010,"lang":"en","type":"article","venue":"","topic":"Migration and Labor Dynamics","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Earnings; Immigration; Unemployment; Affect (linguistics); Unemployment rate; China","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002345325,0.0002581934,0.0004482032,0.0008716633,0.0007864689,0.001561239,0.0005792908,0.0008972312,0.009791723],"category_scores_gemma":[0.01099904,0.0001535542,0.001000702,0.0008786894,0.0006613085,0.0009971034,0.0009112071,0.0008817847,0.001616418],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003829614,"about_ca_system_score_gemma":0.000713962,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01685065,"about_ca_topic_score_gemma":0.0281419,"domain_scores_codex":[0.9991753,0.0003105579,0.00004709428,0.0001138296,0.00008754461,0.0002657838],"domain_scores_gemma":[0.9961383,0.0009403338,0.001260695,0.0002201549,0.0003760254,0.001064531],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002128788,0.00006948172,0.9910036,0.00002428938,0.0001346227,0.0001372762,0.0004577132,0.00006354542,0.00007666313,0.000314311,0.0008322578,0.00667342],"study_design_scores_gemma":[0.000008137937,0.000103817,0.9970854,0.00005610578,0.00004234186,0.00007406352,0.001190745,0.0001073843,0.00003448181,0.0004303542,0.0008576919,0.000009436391],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9880086,0.00186099,0.0001461332,0.002254903,0.0001324225,0.00001579269,0.001192729,0.000009665198,0.006378803],"genre_scores_gemma":[0.9971106,0.0004502271,0.00006363851,0.0002654691,0.00004434252,0.000007606373,0.000609121,0.000009235014,0.001439643],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01685065,"threshold_uncertainty_score":0.03350514,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008798963947846707,"score_gpt":0.2764571241356976,"score_spread":0.2676581601878509,"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."}}