{"id":"W7164919628","doi":"10.1080/17153379.2025.12558750","title":"High Wire: How China Regulates Big Tech and Governs Its Economy","year":2025,"lang":"en","type":"article","venue":"Pacific Affairs","topic":"COVID-19, Geopolitics, Technology, Migration","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"China; High tech; Chinese economy; World economy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001214417,0.0002071672,0.0001586934,0.0008587697,0.004402303,0.00698022,0.0004756076,0.001293637,0.01234949],"category_scores_gemma":[0.002170845,0.000161947,0.0002098371,0.001744472,0.004275735,0.002793743,0.001881476,0.00189718,0.0008208487],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006952859,"about_ca_system_score_gemma":0.01278411,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1441953,"about_ca_topic_score_gemma":0.2324494,"domain_scores_codex":[0.9991235,0.000192935,0.00001632449,0.00008611388,0.0001992856,0.0003818067],"domain_scores_gemma":[0.999123,0.0001798389,0.00009218371,0.00008768425,0.0002413633,0.000275999],"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":[0.00007497166,0.00005260437,0.0327927,0.00004233601,0.00003933484,0.0004199599,0.01371642,0.001123565,0.0009111711,0.8392234,0.07973192,0.03187157],"study_design_scores_gemma":[0.00005417735,0.0001095549,0.1011075,0.0001615257,0.0001045063,0.0000916978,0.02059622,0.00466407,0.001873807,0.1808892,0.690219,0.0001288021],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3390224,0.0008251034,0.003249905,0.03207601,0.0004309399,0.00005137085,0.0003349222,0.0001615695,0.6238477],"genre_scores_gemma":[0.9077633,0.0002780634,0.0003038048,0.002987992,0.00008416881,0.00002671908,0.00006662335,0.00005595031,0.08843344],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1441953,"threshold_uncertainty_score":0.286712,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01438829554904287,"score_gpt":0.2633780972117816,"score_spread":0.2489898016627388,"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."}}