{"id":"W4321125754","doi":"10.2139/ssrn.4360341","title":"Man vs. Machine: Technological Promise and Political Limits of Automated Regulation Enforcement","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Regulation and Compliance Studies","field":"Business, Management and Accounting","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Impact","funders":"","keywords":"Politics; Enforcement; Law and economics; Business; Computer security; Political science; Risk analysis (engineering); Computer science; Economics; Law","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006240006,0.0001129289,0.0001623144,0.0002439095,0.0002008689,0.00006683351,0.0001182314,0.00005545217,0.00003584516],"category_scores_gemma":[0.00008126343,0.00008921037,0.00004967525,0.000420067,0.00009581171,0.0002475048,0.00008336618,0.0003161991,0.00004257186],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001064726,"about_ca_system_score_gemma":0.00006313816,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003306008,"about_ca_topic_score_gemma":0.00005114204,"domain_scores_codex":[0.9984285,0.00001011724,0.0002593605,0.0001379934,0.0002213615,0.0009426434],"domain_scores_gemma":[0.9996321,0.00001688991,0.0001533922,0.00009067803,0.00009434368,0.00001257976],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00004452395,0.00002366298,0.01017401,0.00003040501,0.0000482866,0.000001426651,0.000007854575,0.00004937873,0.000354573,0.9801305,0.0004184989,0.008716914],"study_design_scores_gemma":[0.001492094,0.0001232862,0.192957,0.00008137996,0.00007885082,0.00006862183,0.001272953,0.0726008,0.0001813591,0.7220765,0.008759438,0.000307771],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9765692,0.0004099801,0.0009588659,0.009327559,0.0001270945,0.0003241248,0.000001039803,0.0007895496,0.01149261],"genre_scores_gemma":[0.9987642,0.0001879708,0.00002868572,0.0001411974,0.0001550509,0.00000724565,0.000008597121,0.00001116585,0.0006959182],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.258054,"threshold_uncertainty_score":0.3637893,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01643494839139756,"score_gpt":0.2564977147850577,"score_spread":0.2400627663936601,"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."}}