{"id":"W1497317294","doi":"","title":"Teaching How to Discriminate: Globalization, Prejudice, and Textbooks.","year":2011,"lang":"en","type":"article","venue":"Teacher education quarterly (Claremont, Calif.)","topic":"Global Education and Multiculturalism","field":"Social Sciences","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Globalization; Foreign language; Language policy; Language education; Pedagogy; Sociology; Politics; Sociology of language; Ideology; Language assessment; Government (linguistics); First language; Political science; Comprehension approach; Linguistics; Law","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006463486,0.0002443804,0.0002079791,0.0001411063,0.0009136464,0.0003163745,0.0003500511,0.0001719871,0.0003958527],"category_scores_gemma":[0.0003796502,0.000233244,0.00006759998,0.0002702708,0.0001800617,0.0006374196,0.00002364442,0.0002235559,0.0001372883],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002996573,"about_ca_system_score_gemma":0.0004234689,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0443865,"about_ca_topic_score_gemma":0.007820567,"domain_scores_codex":[0.9978738,0.0004760605,0.0002945577,0.0004972905,0.0003913258,0.0004670063],"domain_scores_gemma":[0.9984295,0.00002894988,0.0001592915,0.0003382089,0.000424697,0.0006193905],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001276317,0.0005036598,0.003548683,0.00002273769,0.00001951999,7.179599e-7,0.7736365,1.40847e-7,0.0001426942,0.04344517,0.07323524,0.1054322],"study_design_scores_gemma":[0.0002699216,0.0001116736,0.0586345,0.00006002918,0.00007955419,0.000007279337,0.3959341,0.00001628717,0.00003399502,0.003374285,0.5409636,0.0005148028],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7768757,0.0006584584,0.001323221,0.05013488,0.002952274,0.001698587,0.00002547168,0.0005335415,0.1657978],"genre_scores_gemma":[0.9654028,0.00001545535,0.003141011,0.002517414,0.0004583383,0.00008049198,0.00003761036,0.00002418795,0.02832263],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4677283,"threshold_uncertainty_score":0.961977,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03580935432271432,"score_gpt":0.3275799349777642,"score_spread":0.2917705806550499,"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."}}