{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009012239,0.0002994812,0.0003682124,0.0005946408,0.0008168459,0.002817099,0.0004860329,0.0008138189,0.006647244],"category_scores_gemma":[0.004308158,0.000153401,0.0004359332,0.0008660441,0.003087805,0.001612535,0.001869388,0.0007279332,0.0003762751],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001665667,"about_ca_system_score_gemma":0.001341496,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01179846,"about_ca_topic_score_gemma":0.0101057,"domain_scores_codex":[0.9992396,0.0003836629,0.00002899453,0.0001101565,0.00008937268,0.0001483099],"domain_scores_gemma":[0.9986753,0.0005821833,0.0003108531,0.0001280381,0.00009866374,0.0002049707],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002929686,0.000382011,0.1893476,0.0004445976,0.0002072738,0.0006528134,0.006718699,0.03191359,0.001650687,0.5949178,0.002166373,0.1713055],"study_design_scores_gemma":[0.00006721402,0.0003604038,0.2177081,0.000653338,0.000127518,0.0005004923,0.009681532,0.04812007,0.0008967708,0.6959727,0.02582351,0.00008843756],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8926727,0.002368802,0.01723742,0.003516427,0.00005376775,0.00007669375,0.0002321603,0.00003151106,0.08381054],"genre_scores_gemma":[0.9937727,0.0009916042,0.001290791,0.0001183336,0.00001813485,0.00002147108,0.00004023207,0.000003480373,0.003743371],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01179846,"threshold_uncertainty_score":0.02345961,"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."}}