{"id":"W2977253486","doi":"10.5089/9781498320450.001","title":"Manufacturing Jobs and Inequality","year":2019,"lang":"en","type":"article","venue":"IMF Working Paper","topic":"Labor market dynamics and wage inequality","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Stylized fact; Inequality; Economics; Labour economics; Distribution (mathematics); Wage; Income distribution; Economic inequality; Manufacturing sector; Wage inequality; Quarter (Canadian coin); Tertiary sector of the economy; Demographic economics; Macroeconomics; Economy","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":[0.0003335617,0.0001535151,0.0002046208,0.0008353943,0.0008919214,0.001361797,0.0003942624,0.0005206029,0.01667217],"category_scores_gemma":[0.001724181,0.00009051409,0.0003726777,0.001394974,0.0005276466,0.000987185,0.001185789,0.0008539415,0.0005809333],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001201286,"about_ca_system_score_gemma":0.0004729868,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01494329,"about_ca_topic_score_gemma":0.01838942,"domain_scores_codex":[0.9997066,0.00003796166,0.000006485363,0.000029785,0.0000316199,0.0001877013],"domain_scores_gemma":[0.9992767,0.0002272763,0.000254344,0.00004416028,0.00006788088,0.0001296091],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001940114,0.0002513355,0.6032761,0.0001601543,0.00009696161,0.0007102653,0.001448723,0.0308294,0.0008080049,0.2939907,0.01345502,0.05477942],"study_design_scores_gemma":[0.00007465734,0.0002243662,0.7547244,0.0002710213,0.00007379009,0.0003966271,0.004575173,0.05705294,0.001014869,0.134198,0.04735304,0.00004115168],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8997701,0.001392202,0.004460112,0.005846102,0.0001194986,0.00003007908,0.001956871,0.00003530041,0.08638974],"genre_scores_gemma":[0.9965028,0.0002621579,0.0002656666,0.0001759308,0.00004458225,0.000008801618,0.0002694897,0.000004290122,0.00246634],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01667217,"threshold_uncertainty_score":0.05577397,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02465899586052538,"score_gpt":0.218884536123099,"score_spread":0.1942255402625736,"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."}}