{"id":"W4310989650","doi":"10.1111/gove.12751","title":"Sorting citizens: Governing via China's social credit system","year":2022,"lang":"en","type":"article","venue":"Governance","topic":"China's Socioeconomic Reforms and Governance","field":"Social Sciences","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"Global Affairs Canada; University of Toronto","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Authoritarianism; State (computer science); Construct (python library); China; Politics; Sociology; Public relations; Loyalty; Ideal (ethics); Misconduct; Political science; Law; Democracy; Computer science","routes":{"ca_aff":true,"ca_fund":true,"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":["sts"],"consensus_categories":[],"category_scores_codex":[0.001147356,0.0002085986,0.0003482453,0.00001729809,0.003902996,0.0001258096,0.0007024112,0.00008905458,0.0008167903],"category_scores_gemma":[0.0001379891,0.0002296461,0.0002303672,0.0002710348,0.0001885681,0.0004060939,0.0003306878,0.0005116189,0.0001260689],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002856364,"about_ca_system_score_gemma":0.0003122202,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0143861,"about_ca_topic_score_gemma":0.0009841302,"domain_scores_codex":[0.9971972,0.0001803781,0.0004498535,0.0004720424,0.0009889584,0.0007115279],"domain_scores_gemma":[0.9986065,0.00006968233,0.0009369298,0.000236676,0.00003806032,0.0001121325],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001455553,0.0001726462,0.02363862,0.0001704289,0.0001472536,0.0001574865,0.09346958,0.0009127318,0.0004375351,0.7260067,0.09702466,0.05771674],"study_design_scores_gemma":[0.0009976778,0.00006860215,0.1067709,0.00005083949,0.00002748441,0.00002282196,0.01458118,0.001247051,0.00003129545,0.003020693,0.8724449,0.0007366198],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7841084,0.0007541476,0.0004658042,0.003510484,0.0028977,0.0003911704,0.0003156152,0.0003572353,0.2071995],"genre_scores_gemma":[0.9866284,0.00009074061,0.0001349692,0.0003309469,0.001894493,0.00008702936,0.000009379019,0.00003795006,0.01078611],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7754202,"threshold_uncertainty_score":0.9973938,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00928440128212598,"score_gpt":0.2434207335028057,"score_spread":0.2341363322206798,"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."}}