{"id":"W2219187693","doi":"","title":"The Barriers to Occupational Mobility: An Aggregate Analysis","year":2014,"lang":"en","type":"article","venue":"2014 Meeting Papers","topic":"Global trade and economics","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Counterfactual thinking; Task (project management); Current Population Survey; Sample (material); Population; Econometrics; Gravity equation; Set (abstract data type); Aggregate (composite); Demographic economics; Variable (mathematics); Computer science; Economics; Psychology; Demography; Geography; Social psychology; Mathematics; Sociology","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":[0.0009184959,0.000191662,0.000781008,0.002182651,0.0004231923,0.001764549,0.000420359,0.0005426412,0.004956252],"category_scores_gemma":[0.004019026,0.0002173968,0.0006600728,0.002711346,0.0003937987,0.001187899,0.001391506,0.0006255065,0.0004577462],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008183538,"about_ca_system_score_gemma":0.0003908914,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01189777,"about_ca_topic_score_gemma":0.008657722,"domain_scores_codex":[0.999383,0.0001701944,0.00003090857,0.0001114066,0.0001606026,0.0001439034],"domain_scores_gemma":[0.9979267,0.0008210223,0.0006356642,0.0002587432,0.0002167595,0.0001411774],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003665688,0.0002894247,0.7899684,0.0002063588,0.0006403269,0.0006096408,0.002204997,0.09158245,0.001103333,0.06865784,0.006723303,0.03764742],"study_design_scores_gemma":[0.00002445973,0.0002061647,0.8970366,0.0000566488,0.0003103093,0.0001971021,0.002420322,0.0651147,0.0002964838,0.02284471,0.01145143,0.00004102391],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9807419,0.0003780424,0.005971265,0.0004703909,0.000008541067,0.00003588983,0.003236131,0.00003653998,0.009121393],"genre_scores_gemma":[0.9969408,0.0002092394,0.0005479305,0.00002615055,0.00001973761,0.00002575588,0.001278679,0.000005046236,0.0009465829],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01189777,"threshold_uncertainty_score":0.02365702,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0262269627431499,"score_gpt":0.2242261504637928,"score_spread":0.1979991877206429,"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."}}