{"id":"W1569514844","doi":"","title":"Union Negotiation and Wage Inequality in Argentina: An Empirical Analysis of Recent Trends","year":2013,"lang":"en","type":"article","venue":"El Servicio de Difusión de la Creación Intelectual (National University of La Plata)","topic":"Labor Movements and Unions","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"International Development Research Centre","keywords":"Negotiation; Wage; Inequality; Economics; Wage inequality; Income distribution; Labour economics; Union density; Distribution (mathematics); Period (music); Political science; Law","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001355193,0.00009509854,0.0002250469,0.0005372544,0.0001610772,0.00003112105,0.0002259795,0.0001694234,0.001536458],"category_scores_gemma":[0.0002742044,0.0001081616,0.00006562619,0.001403947,0.0002088396,0.0003937524,0.00006939689,0.0001551539,7.388836e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002747286,"about_ca_system_score_gemma":0.0002073387,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.03284506,"about_ca_topic_score_gemma":0.04334676,"domain_scores_codex":[0.9981554,0.0008336633,0.0002065221,0.0002022055,0.0003958061,0.0002064626],"domain_scores_gemma":[0.9986895,0.0005494878,0.0001558378,0.0001034995,0.0003771647,0.0001245337],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001121264,0.001100267,0.7386786,0.0000178791,0.0004544077,0.000008082479,0.0847814,0.001115423,0.001858748,0.1589573,0.0005156595,0.01240008],"study_design_scores_gemma":[0.0004096674,0.00004314819,0.9754777,0.000009613887,0.0001052717,4.869489e-7,0.00756991,0.007181036,0.00007013293,0.002243786,0.006777011,0.000112269],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9878958,0.00001196507,0.0008803578,0.0008585895,0.00001610649,0.00008012537,0.00008271216,0.0000196478,0.0101547],"genre_scores_gemma":[0.9989339,0.0001518004,0.0003809504,0.0001779538,0.00001851924,6.730694e-7,0.0002122382,0.00000466754,0.0001192576],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.236799,"threshold_uncertainty_score":0.9993763,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02362186871093365,"score_gpt":0.3263183019518974,"score_spread":0.3026964332409638,"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."}}