{"id":"W4405920878","doi":"10.1257/app.20230403","title":"Careers and Intergenerational Income Mobility","year":2024,"lang":"en","type":"article","venue":"American Economic Journal Applied Economics","topic":"Intergenerational and Educational Inequality Studies","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; Université du Québec à Montréal","funders":"","keywords":"Microdata (statistics); Demographic economics; Economics; Persistence (discontinuity); Social mobility; Income distribution; Labour economics; Occupational mobility; Socioeconomic status; Census; Population; Demography; Sociology; Inequality","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":[0.0006263395,0.0001352149,0.0001475457,0.001856777,0.0006774072,0.0009608855,0.0002974878,0.0002355723,0.006129528],"category_scores_gemma":[0.005236586,0.0001311871,0.0002046259,0.002835185,0.0003882502,0.0006829203,0.001221462,0.0004459585,0.0006930973],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006741497,"about_ca_system_score_gemma":0.0003494178,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01703192,"about_ca_topic_score_gemma":0.03137035,"domain_scores_codex":[0.9996767,0.0001141512,0.00002301346,0.00004138025,0.00005854051,0.00008628218],"domain_scores_gemma":[0.9964309,0.001033478,0.001788193,0.0001850003,0.0002247983,0.0003376658],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005544561,0.00004139138,0.9752507,0.00001999992,0.00005690289,0.0001103432,0.0006683726,0.001469183,0.00006386846,0.005041252,0.001102702,0.0161198],"study_design_scores_gemma":[0.000005119173,0.00002666178,0.9875229,0.00004950133,0.00001949598,0.0001469713,0.001446462,0.003256624,0.00006705909,0.003109216,0.004340505,0.000009478884],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9911585,0.000743878,0.0006924639,0.0005366988,0.00001146332,0.00001076552,0.002368634,0.00001122016,0.004466396],"genre_scores_gemma":[0.9971867,0.0003389388,0.0001836773,0.00001380448,0.000006963452,0.000005672666,0.001004036,0.000002079967,0.001258027],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01703192,"threshold_uncertainty_score":0.03386557,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01925366331784955,"score_gpt":0.3056186382459067,"score_spread":0.2863649749280572,"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."}}