{"id":"W3115805849","doi":"10.15353/rea.v13i2.4045","title":"Cultural Assimilation: Learning and Sorting","year":2021,"lang":"en","type":"article","venue":"Review of Economic Analysis","topic":"Migration and Labor Dynamics","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Immigration; Incentive; Neighbourhood (mathematics); Demographic economics; Cultural assimilation; Species richness; Sorting; Ethnic group; Geography; Economics; Economic geography; Political science; Ecology; Microeconomics; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004682794,0.00003354784,0.0002169674,0.00002819,0.0001148893,0.00002455235,0.00003174067,0.00001965518,0.001775533],"category_scores_gemma":[0.0002140658,0.00003170091,0.0001238158,0.0002552936,0.00003776568,0.00008632194,0.00001197948,0.00003548574,0.000008004879],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003736205,"about_ca_system_score_gemma":0.00006796985,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001051818,"about_ca_topic_score_gemma":0.004022056,"domain_scores_codex":[0.9994451,0.0001237908,0.0002311436,0.00009621303,0.0000451336,0.00005855622],"domain_scores_gemma":[0.9996237,0.00004638585,0.0001798762,0.00004982209,0.00006632445,0.00003386087],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000002050572,0.00003234638,0.6323892,0.001680172,0.001990847,0.000003481219,0.01254077,0.004462981,0.00005100544,0.2340966,0.001460983,0.1112896],"study_design_scores_gemma":[0.0002277079,0.00001333748,0.01501214,0.001247475,0.003852993,0.000001348564,0.01947549,0.08466995,0.00002947232,0.0006173831,0.874383,0.0004696489],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5028312,0.2473632,0.002137892,0.01319511,0.0001592421,0.0002554876,0.00001321177,0.00007014204,0.2339745],"genre_scores_gemma":[0.6408855,0.3538569,0.0006331755,0.000315215,0.00006306414,0.000002104019,0.00004194875,0.000002588332,0.004199529],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8729221,"threshold_uncertainty_score":0.999137,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02198847454624164,"score_gpt":0.3551497389949236,"score_spread":0.3331612644486819,"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."}}