{"id":"W2123925592","doi":"10.3968/j.css.1923669720100604.025","title":"Youth Unemployment in Nigeria: Causes and Related Issues","year":2010,"lang":"en","type":"article","venue":"Canadian social science","topic":"Unemployment and Economic Growth","field":"Economics, Econometrics and Finance","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Nigerians; Youth unemployment; Unemployment; Livelihood; Loan; Economic growth; Population; Business; Sociology; Political science; Economics; Agriculture; Geography; Finance","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.0008430262,0.0002320777,0.0003988916,0.002310778,0.002922342,0.001826801,0.0003906703,0.001434832,0.003016049],"category_scores_gemma":[0.00189047,0.0002617665,0.0004237468,0.002261873,0.001228271,0.00116457,0.001450632,0.001003411,0.0001574384],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00173586,"about_ca_system_score_gemma":0.002883176,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02146338,"about_ca_topic_score_gemma":0.035492,"domain_scores_codex":[0.999292,0.0002055075,0.00009351521,0.0000593095,0.0001108284,0.0002387872],"domain_scores_gemma":[0.9986848,0.0003715115,0.000414474,0.00002594231,0.0002157383,0.0002876045],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001667166,0.0002584623,0.811712,0.002610601,0.00007269521,0.01337824,0.02152341,0.0004587602,0.0004289834,0.01635246,0.01244344,0.1205943],"study_design_scores_gemma":[0.00001442996,0.0002098031,0.7533208,0.008231797,0.0001362091,0.01651618,0.1498839,0.0007394271,0.0003641989,0.01157882,0.05892097,0.00008348349],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7429149,0.1827485,0.0004982958,0.05013083,0.001804252,0.00008819369,0.0008850886,0.00003578897,0.02089421],"genre_scores_gemma":[0.930179,0.06599942,0.0001968167,0.001398978,0.0006710413,0.00003126197,0.0001700299,0.000006793062,0.001346662],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02146338,"threshold_uncertainty_score":0.04267687,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02283704183069333,"score_gpt":0.2203607348844172,"score_spread":0.1975236930537239,"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."}}