{"id":"W4313886875","doi":"10.32920/ryerson.14638545.v2","title":"Intergenerational Transmission of Abilities and Self Selection of Mexican Immigrants","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Migration and Labor Dynamics","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Earnings; Immigration; Human capital; Selection (genetic algorithm); Demographic economics; Positive selection; Census; Psychology; Correlation; Economics; Developmental psychology; Demography; Sociology; Geography; Economic growth; Population; Computer science; Mathematics; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001094431,0.0001745339,0.0002297467,0.0006290126,0.0005405392,0.001226164,0.0003568174,0.0004546372,0.0039668],"category_scores_gemma":[0.003236514,0.0001766398,0.0004022735,0.0005875693,0.0004365362,0.0005029773,0.0008838232,0.0004062575,0.0002246943],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005932432,"about_ca_system_score_gemma":0.0002799093,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0161602,"about_ca_topic_score_gemma":0.01137264,"domain_scores_codex":[0.9997078,0.0001083071,0.00001687914,0.00005458879,0.00002910544,0.00008337],"domain_scores_gemma":[0.9985926,0.0004488924,0.0006713183,0.0001399517,0.00005114309,0.00009617263],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002501137,0.0002487379,0.9268759,0.00004622018,0.0001947383,0.001629313,0.006473568,0.007079576,0.0007914772,0.02482385,0.001082145,0.03050439],"study_design_scores_gemma":[0.00006611011,0.0002163623,0.9429302,0.00009306106,0.0002264819,0.0006217157,0.008096987,0.02618527,0.0004982874,0.01636569,0.004654218,0.00004568452],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967319,0.0001522871,0.0006718219,0.0002678468,0.000006142991,0.000008724433,0.00009729091,0.000005212131,0.002058803],"genre_scores_gemma":[0.9980956,0.0002203123,0.0002097735,0.00003533563,0.000006983245,0.000009165499,0.00008071422,0.000001588029,0.001340621],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0161602,"threshold_uncertainty_score":0.03213227,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02210720174028962,"score_gpt":0.3048343702110466,"score_spread":0.282727168470757,"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."}}