{"id":"W4385796054","doi":"10.2139/ssrn.4529394","title":"From Discrimination to Integration: A History of Chinese Immigration in Canada","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Migration, Ethnicity, and Economy","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Immigration; Political science; History; Demographic economics; Law; Economics","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":[0.001377012,0.0002523717,0.000409247,0.002586158,0.0268816,0.006458075,0.001191652,0.002479094,0.005124169],"category_scores_gemma":[0.003520405,0.0002578979,0.0002852711,0.007424886,0.0145617,0.001993545,0.005027756,0.004798261,0.0001665343],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.07518405,"about_ca_system_score_gemma":0.1443374,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9845483,"about_ca_topic_score_gemma":0.9929661,"domain_scores_codex":[0.9978911,0.0002093632,0.00005822212,0.000165609,0.0003131404,0.001362606],"domain_scores_gemma":[0.9975961,0.0003641733,0.0002118499,0.00006555266,0.0006905827,0.001071733],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002577623,0.0001617474,0.08546884,0.0002897879,0.00005992244,0.00429549,0.6300154,0.0002928636,0.0005787234,0.1523082,0.02092333,0.1053479],"study_design_scores_gemma":[0.00002862495,0.00007821915,0.1978975,0.0009478329,0.00007795939,0.001424722,0.4256459,0.0003461125,0.0005043424,0.00690678,0.3659678,0.0001741792],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8801411,0.01553692,0.0002706976,0.02740402,0.000602739,0.00005255621,0.0002538595,0.00001868247,0.07571936],"genre_scores_gemma":[0.9821207,0.004625644,0.0001068638,0.003045689,0.0001024461,0.00001203431,0.00005675161,0.00001694448,0.009913041],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07518405,"threshold_uncertainty_score":0.545501,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01187751888284329,"score_gpt":0.2591602864690666,"score_spread":0.2472827675862233,"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."}}