{"id":"W4388837653","doi":"10.2139/ssrn.4609113","title":"Trusting Talent: Cross-Country Differences in Hiring","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Financial Literacy, Pension, Retirement Analysis","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Cross country; Business; Demographic economics; Economics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002241718,0.0002225388,0.000435714,0.0009597834,0.0007521051,0.001738892,0.0005721241,0.0007661763,0.01115848],"category_scores_gemma":[0.006643214,0.0002442505,0.0006922071,0.001311502,0.0006083724,0.0009904008,0.001719582,0.001158497,0.001327811],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003140365,"about_ca_system_score_gemma":0.0004669037,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01655912,"about_ca_topic_score_gemma":0.02670765,"domain_scores_codex":[0.9983979,0.0003635791,0.0001016245,0.0002981714,0.000166823,0.0006718736],"domain_scores_gemma":[0.98738,0.004612674,0.003224781,0.0007378131,0.0009030118,0.003141661],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004406864,0.0001665757,0.9869663,0.00002618209,0.000329059,0.0003388958,0.00348161,0.0002774043,0.0006200677,0.0004148881,0.000748703,0.006189567],"study_design_scores_gemma":[0.000006478869,0.00008127877,0.996274,0.00001445002,0.0000399443,0.00005916489,0.002835585,0.00009281618,0.000093215,0.00009338682,0.0004014614,0.000008179457],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9974923,0.0002572462,0.00009900043,0.0001653909,0.00002835336,0.000004682865,0.0001976555,0.000004094244,0.001751317],"genre_scores_gemma":[0.9987168,0.00004607103,0.0000226504,0.00003322289,0.000007238412,0.000002020098,0.0001388004,0.000004533032,0.001028689],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01655912,"threshold_uncertainty_score":0.0373289,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01356505591375341,"score_gpt":0.2436549830375183,"score_spread":0.2300899271237649,"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."}}