{"id":"W2938062673","doi":"10.1080/07360932.2020.1800500","title":"Selling Hollywood to China","year":2020,"lang":"en","type":"article","venue":"Forum for Social Economics","topic":"Cultural Industries and Urban Development","field":"Social Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Hollywood; Movie theater; China; Film industry; Censorship; Communism; Power (physics); Advertising; Foreign policy; Economic power; Politics; Political economy; Economics; Market economy; Political science; Business; Law; History","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001330995,0.00008217644,0.0001460659,0.00001295208,0.0008703682,0.0001146536,0.0001863449,0.0001043091,0.0001527269],"category_scores_gemma":[0.00006769708,0.00009029308,0.00009988711,0.0001050537,0.00004334108,0.000163994,0.00004390001,0.0000695894,0.00006695215],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001533147,"about_ca_system_score_gemma":0.0001513483,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003230276,"about_ca_topic_score_gemma":0.0009615775,"domain_scores_codex":[0.9992566,0.00001084792,0.000165478,0.0001776708,0.00004824371,0.0003411277],"domain_scores_gemma":[0.9996703,0.00002054917,0.00005750053,0.00003293093,0.00003108453,0.0001875834],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006476053,0.00001990329,0.0006245235,0.000009423391,0.00005493182,6.276282e-7,0.05959383,0.0002781097,0.00001750515,0.19634,0.6876043,0.05539212],"study_design_scores_gemma":[0.0001640321,0.00003843296,0.0001501509,0.000001563174,0.000005520911,5.606715e-8,0.01062288,0.0001088205,0.00007350524,0.001969539,0.9867183,0.0001471845],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.3172676,0.00004794401,0.002193252,0.637652,0.001216465,0.00126209,0.0001579327,0.0002012581,0.04000146],"genre_scores_gemma":[0.9708126,0.00005890742,0.001960686,0.01110209,0.002969732,0.00007147083,0.00003443952,0.00003149176,0.0129586],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.653545,"threshold_uncertainty_score":0.6694256,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0697682273227062,"score_gpt":0.2931828520070776,"score_spread":0.2234146246843714,"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."}}