{"id":"W4324029325","doi":"10.1093/qje/qjad012","title":"AI-tocracy","year":2023,"lang":"en","type":"article","venue":"The Quarterly Journal of Economics","topic":"Culture, Economy, and Development Studies","field":"Social Sciences","cited_by":109,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Institute for Advanced Research","funders":"Harvard Data Science Initiative, Harvard University; British Academy; National Science Foundation","keywords":"Unrest; Context (archaeology); Politics; Procurement; Government (linguistics); Autocracy; Economics; China; Political science; Management; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000771021,0.0001429459,0.0002354189,0.001464114,0.001790607,0.001858475,0.0004551033,0.0004016501,0.05267282],"category_scores_gemma":[0.00425156,0.000082585,0.0002695796,0.002081991,0.002040704,0.001166855,0.001641453,0.0007277646,0.002139008],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002515205,"about_ca_system_score_gemma":0.002067132,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0301757,"about_ca_topic_score_gemma":0.03469133,"domain_scores_codex":[0.9987668,0.0001895031,0.00005740709,0.0002195436,0.0003933301,0.0003733747],"domain_scores_gemma":[0.9953139,0.0009345663,0.001504473,0.00069638,0.000829332,0.0007212972],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002083066,0.000278322,0.5043603,0.0004015161,0.0001045512,0.0009784801,0.007151518,0.002333468,0.001710237,0.2578602,0.02771432,0.1968988],"study_design_scores_gemma":[0.00002665596,0.0001286998,0.7770416,0.0001643858,0.0000376858,0.000282636,0.004698781,0.003490801,0.0007498265,0.02535475,0.1879925,0.00003183113],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5256354,0.001112318,0.002252214,0.003400411,0.0001465051,0.0001041451,0.00137003,0.0001039952,0.4658751],"genre_scores_gemma":[0.9838361,0.0002076434,0.0002301143,0.0002836791,0.00005550541,0.00002563625,0.0002698232,0.000009874091,0.01508153],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05267282,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03999743824012492,"score_gpt":0.3055660320114696,"score_spread":0.2655685937713447,"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."}}