{"id":"W3123303565","doi":"","title":"When Politics Froze Fashion: The Effect of the Cultural Revolution on Naming in Beijing","year":2014,"lang":"en","type":"article","venue":"DSpace@MIT (Massachusetts Institute of Technology)","topic":"Fashion and Cultural Textiles","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"University of Chicago","keywords":"Politics; Ideology; Conformity; Authoritarianism; Beijing; Popularity; Limiting; Expression (computer science); Political economy; Positive economics; Sociology; Political science; Social psychology; Law; Psychology; Democracy; Economics","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":[0.00122257,0.0001441438,0.0003906687,0.0006084805,0.003982174,0.0034039,0.0008579044,0.001154768,0.007447015],"category_scores_gemma":[0.002923291,0.0001764489,0.0002795897,0.001572533,0.004702211,0.001639664,0.002310612,0.001372033,0.000342906],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005293261,"about_ca_system_score_gemma":0.001556157,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09419239,"about_ca_topic_score_gemma":0.223205,"domain_scores_codex":[0.9987578,0.0004912449,0.00003559388,0.0001017127,0.0001109875,0.0005026177],"domain_scores_gemma":[0.9974871,0.0007813536,0.0009022683,0.0001314246,0.000161558,0.0005362179],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.0009196426,0.0005355581,0.7203869,0.00009950547,0.0001478245,0.002983371,0.2219742,0.000884162,0.003982763,0.01663404,0.003604368,0.02784766],"study_design_scores_gemma":[0.00001554864,0.0001043154,0.8546175,0.00001599814,0.00001927895,0.00006669987,0.1390016,0.0002175526,0.0003008966,0.000922534,0.004699416,0.00001859243],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9937071,0.00005145018,0.00001905777,0.0006470097,0.000007502406,0.000002534542,0.00001224273,0.000002509088,0.005550606],"genre_scores_gemma":[0.9992546,0.00002766962,0.000007127058,0.00003509038,0.000004142628,0.000001620878,0.00001135179,0.000002084057,0.0006562198],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09419239,"threshold_uncertainty_score":0.1872882,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01410744962930219,"score_gpt":0.2272207231457306,"score_spread":0.2131132735164284,"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."}}