{"id":"W2009004028","doi":"10.1136/bmj.c2154","title":"The importance of government policies in reducing employment related health inequalities","year":2010,"lang":"en","type":"article","venue":"BMJ","topic":"Employment and Welfare Studies","field":"Health Professions","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"British Heart Foundation","keywords":"Inequality; Government (linguistics); Welfare state; Welfare; State (computer science); Public economics; Health equity; Economics; Labour economics; Political science; Economic growth; Health care; Law; Politics; Computer science; Market economy","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002134385,0.0001041344,0.0002429329,0.00002583183,0.0005892498,0.000004012306,0.0001400566,0.00006705502,0.00006848555],"category_scores_gemma":[0.0003840165,0.00006823162,0.00004034034,0.0001326692,0.0000980421,0.00004364101,0.0001519047,0.0004359326,0.00001233738],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000151617,"about_ca_system_score_gemma":0.0001550534,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004292734,"about_ca_topic_score_gemma":0.01684987,"domain_scores_codex":[0.9978924,0.0002539977,0.0009657987,0.0001368849,0.0003331449,0.0004178145],"domain_scores_gemma":[0.998594,0.0004915188,0.0004943542,0.000331814,0.00004045114,0.00004779831],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002654819,0.0000332653,0.8818065,0.00007237148,0.00002411392,7.992633e-7,0.01893832,0.000002060914,0.0001849742,0.04624736,0.05163449,0.001029205],"study_design_scores_gemma":[0.0005533334,0.00009097525,0.9129446,0.0002691779,0.000004570777,5.659118e-7,0.02082898,0.000008823502,0.00008602114,0.00290627,0.06219053,0.0001161204],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8956049,0.0004378246,0.000001083184,0.08771839,0.0007943184,0.0007611003,0.00002098209,0.00003184251,0.01462957],"genre_scores_gemma":[0.9879616,0.0002867715,0.00005902889,0.001047874,0.0001650347,0.0001968096,0.00000322117,0.00001509818,0.01026454],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09235673,"threshold_uncertainty_score":0.9402622,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06263585023941665,"score_gpt":0.4361487977894106,"score_spread":0.373512947549994,"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."}}