{"id":"W3045838858","doi":"10.38055/fs010203","title":"Review: Diversity NOW! Fashion & Race with Kimberly Jenkins","year":2019,"lang":"en","type":"article","venue":"Fashion Studies","topic":"Fashion and Cultural Textiles","field":"Arts and Humanities","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Diversity (politics); Representation (politics); Race (biology); Racism; Sociology; Power (physics); Visual arts; Media studies; Gender studies; Art; Anthropology; Political science; Law","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001850721,0.0002808583,0.0004865529,0.00005518184,0.0008136865,0.00008817753,0.0002314363,0.0000407411,0.002829971],"category_scores_gemma":[0.00003856415,0.0001769927,0.0001361645,0.00008272577,0.0002325641,0.0003901998,0.000325953,0.0001879478,0.005806188],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005708178,"about_ca_system_score_gemma":0.00001343897,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001213824,"about_ca_topic_score_gemma":0.003738494,"domain_scores_codex":[0.9986388,0.00007491069,0.0002443531,0.0003714862,0.0003690218,0.0003014169],"domain_scores_gemma":[0.9989979,0.00008192353,0.00015605,0.0003246362,0.0003691108,0.00007037811],"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":[0.00005916504,0.0001668621,0.01088233,0.00162638,0.000517018,0.00001087537,0.1188883,0.000004355087,0.0001159145,0.04896585,0.8163045,0.002458422],"study_design_scores_gemma":[0.0004869126,0.0001682248,0.002076066,0.0008809164,0.0001071962,0.00000446979,0.04445802,9.898184e-7,0.000004855689,0.00004594825,0.9513911,0.0003752737],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9060775,0.006097372,0.000004692638,0.003020672,0.0009212948,0.0005849188,0.00002846887,0.0002668064,0.08299828],"genre_scores_gemma":[0.8187654,0.02010256,0.00004976626,0.003876184,0.000268573,0.00002667919,0.00004266637,0.00002254686,0.1568456],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1350866,"threshold_uncertainty_score":0.9980816,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07231913770651137,"score_gpt":0.2796376286569046,"score_spread":0.2073184909503932,"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."}}