{"id":"W4312265008","doi":"10.2139/ssrn.4260700","title":"AI, Skill, and Productivity: The Case of Taxi Drivers","year":2022,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Impact of AI and Big Data on Business and Society","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Productivity; Context (archaeology); Labour economics; Business; Demographic economics; Engineering; Operations management; Marketing; Economics; Geography; Economic growth","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":[0.001670876,0.000279578,0.000418856,0.001309197,0.002259903,0.003497225,0.0008383823,0.001702671,0.01345129],"category_scores_gemma":[0.008823891,0.0001897031,0.0003522955,0.00223304,0.001646217,0.002780478,0.001632139,0.002293216,0.0006795226],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00238373,"about_ca_system_score_gemma":0.001870344,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1107533,"about_ca_topic_score_gemma":0.1179566,"domain_scores_codex":[0.999453,0.0001853497,0.00001266944,0.00004131863,0.0000481437,0.0002595028],"domain_scores_gemma":[0.9919879,0.004723293,0.0006735995,0.0002668689,0.0006685469,0.001679868],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001109638,0.001295444,0.7504321,0.0001684236,0.0002985463,0.006179169,0.01734836,0.02071904,0.0004862183,0.1333308,0.01639154,0.05224082],"study_design_scores_gemma":[0.0003451062,0.0005598523,0.4237014,0.0002748979,0.0003550658,0.00239259,0.210949,0.1038946,0.0009649922,0.2110582,0.04526302,0.0002412643],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9629529,0.0004708036,0.001068431,0.007343199,0.00003539141,0.00002293814,0.0002817249,0.000009593554,0.02781505],"genre_scores_gemma":[0.9966347,0.0002524559,0.0001585397,0.00009365631,0.00001553858,0.000005523701,0.00005477865,0.000003028526,0.002781915],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1107533,"threshold_uncertainty_score":0.2202172,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03346254354196604,"score_gpt":0.3297580683376328,"score_spread":0.2962955247956667,"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."}}