{"id":"W3130613753","doi":"","title":"A Tale of Two Countries: A Story of the French and US Polarization","year":2017,"lang":"en","type":"article","venue":"RePEc: Research Papers in Economics","topic":"Labor market dynamics and wage inequality","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Université du Québec à Montréal","keywords":"Polarization (electrochemistry); Subsidy; Welfare; Labour economics; Wage; Economics; Context (archaeology); Demographic economics; Geography; Market economy","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002727802,0.0002436128,0.0004455833,0.002499457,0.005665671,0.004833246,0.0003375756,0.001605851,0.002985079],"category_scores_gemma":[0.003824084,0.0001482087,0.000627513,0.002911176,0.003067486,0.002619532,0.00282876,0.001708384,0.0002795417],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005664166,"about_ca_system_score_gemma":0.001657096,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1600532,"about_ca_topic_score_gemma":0.09811606,"domain_scores_codex":[0.998086,0.000786882,0.00003450454,0.0001607323,0.000230628,0.000701364],"domain_scores_gemma":[0.9976628,0.0007966407,0.0004857142,0.0001845498,0.0005161439,0.0003541189],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001232732,0.0002854396,0.4028799,0.0002388001,0.0004344203,0.00498123,0.0838052,0.002523237,0.001882018,0.2504757,0.08148836,0.169773],"study_design_scores_gemma":[0.0001055384,0.0003372526,0.5597124,0.0005531556,0.0001131776,0.00120483,0.09153301,0.001519603,0.0009587309,0.02018838,0.3235633,0.0002105727],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8871909,0.00772102,0.0007096047,0.05447072,0.0003235863,0.00001566189,0.0006267115,0.00004456193,0.04889721],"genre_scores_gemma":[0.9920346,0.001236009,0.0001635226,0.003469776,0.000143526,0.000009713407,0.0001697576,0.00001824736,0.002754855],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1600532,"threshold_uncertainty_score":0.3182433,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02434303832474745,"score_gpt":0.2821982901006347,"score_spread":0.2578552517758873,"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."}}