{"id":"W2903251213","doi":"10.1177/1077800418809129","title":"Unmasking China’s Great Leap Forward and Great Famine (1958-1962) Through <i>Shunkouliu</i> (顺口溜)","year":2018,"lang":"en","type":"article","venue":"Qualitative Inquiry","topic":"Vietnamese History and Culture Studies","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Representativeness heuristic; Famine; China; Rhetoric; Credibility; Scholarship; Sociology; Folklore; Narrative; Positivism; Media studies; History; Social science; Law; Political science; Literature; Anthropology; Psychology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001449091,0.0002083685,0.0001442438,0.0005901336,0.004382193,0.001365493,0.0002233143,0.0004408943,0.002021862],"category_scores_gemma":[0.002088541,0.0001263493,0.00009870406,0.001124843,0.007210866,0.001458954,0.001322664,0.00110404,0.0000719306],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006013079,"about_ca_system_score_gemma":0.003944339,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03888846,"about_ca_topic_score_gemma":0.1074736,"domain_scores_codex":[0.9996356,0.0001779443,0.00001303939,0.00004820993,0.00005134584,0.00007395281],"domain_scores_gemma":[0.9990855,0.0005373023,0.0001150065,0.00007320207,0.00009436462,0.00009451206],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00004667713,0.000009867804,0.01420436,0.0001971217,0.00000720646,0.0009908165,0.9080586,0.000138178,0.00193678,0.05099054,0.002466331,0.0209535],"study_design_scores_gemma":[0.00001248465,0.0001103728,0.06306256,0.0003933664,0.00001719233,0.0003660994,0.7996999,0.0004741642,0.004022655,0.01167672,0.1201236,0.00004087623],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9613317,0.001115091,0.001381486,0.004568439,0.0001160612,0.0000362212,0.00009756157,0.00001351861,0.03133989],"genre_scores_gemma":[0.9959087,0.0002303019,0.0002198055,0.0001387803,0.00001054914,0.00001844723,0.00001828692,0.000004402493,0.00345082],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03888846,"threshold_uncertainty_score":0.07732421,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1057036208313024,"score_gpt":0.4266820668335503,"score_spread":0.320978446002248,"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."}}