{"id":"W2916417388","doi":"10.4102/sajems.v22i1.2104","title":"The unemployed and the formal and informal sectors in South Africa: A macroeconomic analysis","year":2019,"lang":"en","type":"article","venue":"South African Journal of Economic and Management Sciences","topic":"Unemployment and Economic Growth","field":"Economics, Econometrics and Finance","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Credence; Informal sector; Unemployment; Economics; Point (geometry); Quarter (Canadian coin); Demographic economics; Labour economics; Economic growth; Geography; Statistics","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":[],"consensus_categories":[],"category_scores_codex":[0.003182994,0.0001703329,0.0005445143,0.00061172,0.0003533769,0.0004103353,0.0004060773,0.00003629508,0.00004830955],"category_scores_gemma":[0.00001540921,0.000113768,0.0001348459,0.000250744,0.0006926963,0.0007046915,0.0002371098,0.0001340452,0.00002973973],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004999849,"about_ca_system_score_gemma":0.00002170971,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005112584,"about_ca_topic_score_gemma":0.00009899752,"domain_scores_codex":[0.9983039,0.00002662659,0.0009175154,0.0003020938,0.00003640202,0.0004134463],"domain_scores_gemma":[0.9987057,0.0001451378,0.0008727913,0.0001702655,0.00000749475,0.00009855026],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001444526,0.000007719618,0.7298247,0.00001658944,0.0004525703,0.000001194598,0.01078928,0.0009717021,1.150926e-7,0.2569916,0.00003855547,0.0007614788],"study_design_scores_gemma":[0.01083088,0.0006021539,0.8069041,0.00003972853,0.0003949537,0.0000232004,0.07429874,0.0381652,0.000002577243,0.04921455,0.01861867,0.0009052854],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9798125,0.001690355,0.00007760854,0.0006394085,0.0002439149,0.000270547,0.00001462155,0.000004588278,0.01724646],"genre_scores_gemma":[0.9984131,0.0007096941,0.00009825956,0.00009210623,0.00004012815,0.000008736251,4.387428e-7,0.000007137427,0.0006304156],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2077771,"threshold_uncertainty_score":0.4639325,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01608645744110251,"score_gpt":0.195121194006433,"score_spread":0.1790347365653305,"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."}}