{"id":"W2346289171","doi":"","title":"Assessing Economic Mobility: Migrant Communities and First Nations","year":2015,"lang":"en","type":"article","venue":"27th Annual Meeting","topic":"Migration, Ethnicity, and Economy","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Immigration; Economic growth; Development economics; Geography; Business; 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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.001650605,0.00007530655,0.0001199554,0.00007396445,0.001492672,0.0002780197,0.0001338024,0.00005949605,0.00004473784],"category_scores_gemma":[0.0004217094,0.0000811397,0.00002694357,0.00007606269,0.0002329936,0.0009096116,0.00005235506,0.00008858983,0.0000240903],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000121599,"about_ca_system_score_gemma":0.0001929371,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.05232669,"about_ca_topic_score_gemma":0.4783964,"domain_scores_codex":[0.9991782,0.0001936679,0.0001983016,0.0001160451,0.00009619733,0.0002175642],"domain_scores_gemma":[0.9990462,0.000509156,0.00008628276,0.0001130979,0.00009985746,0.0001454263],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.000005826641,0.000050597,0.2026263,0.00003639089,0.00001864002,7.532439e-7,0.7833381,0.0004005104,0.000003453306,0.008418607,0.002971331,0.002129514],"study_design_scores_gemma":[0.0002876713,0.00003212982,0.0142181,0.00007525246,0.00001594708,0.000001718517,0.8416244,0.001257169,0.00002542742,0.002180742,0.1400384,0.0002429879],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9361957,0.0003047482,0.00005045791,0.001335484,0.0002245094,0.0001220488,0.00001307517,0.00006391831,0.06169],"genre_scores_gemma":[0.9987554,0.0001079042,0.0004538071,0.00009343632,0.0002771256,0.00001418092,0.000007827714,0.000006574606,0.0002837221],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4260698,"threshold_uncertainty_score":0.9998072,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05813003926875181,"score_gpt":0.3264982368911747,"score_spread":0.2683681976224229,"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."}}