{"id":"W4312304819","doi":"10.2139/ssrn.4260797","title":"Technological Change and the Finance Wage Premium","year":2022,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Financial Literacy, Pension, Retirement Analysis","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Economics; Wage; Labour 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":[0.0007422868,0.0000967801,0.0001432147,0.001125717,0.0003337958,0.001343694,0.0001624976,0.001277367,0.01613261],"category_scores_gemma":[0.004375601,0.00006868999,0.0002392695,0.0007765616,0.0005961588,0.0008995588,0.0005124796,0.00103189,0.0009447158],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004487703,"about_ca_system_score_gemma":0.000309515,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00335072,"about_ca_topic_score_gemma":0.004354445,"domain_scores_codex":[0.9998286,0.00003279935,0.00001081364,0.00002264426,0.00003668984,0.0000683633],"domain_scores_gemma":[0.9968196,0.001583437,0.0009716906,0.00009698339,0.00009619736,0.0004319765],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00164985,0.001129545,0.7636886,0.0001165875,0.0001189435,0.001697969,0.001856832,0.002824346,0.002327197,0.0821811,0.006551576,0.1358573],"study_design_scores_gemma":[0.00007967598,0.0002690593,0.9518959,0.00005269923,0.0000552071,0.000422798,0.0008403775,0.002199982,0.0004411327,0.03562745,0.008095003,0.00002079971],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9742495,0.003182747,0.0003294058,0.004411785,0.00006054914,0.000005588231,0.0002212066,0.00001306251,0.01752611],"genre_scores_gemma":[0.9959077,0.0005432228,0.000034333,0.0000982091,0.000139497,0.000001063533,0.00005104247,0.000002440319,0.003222605],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01613261,"threshold_uncertainty_score":0.05396903,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01210043430479261,"score_gpt":0.1991084390849084,"score_spread":0.1870080047801158,"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."}}