{"id":"W2560365002","doi":"10.1080/09500782.2016.1261892","title":"Language education policy and multilingual assessment","year":2016,"lang":"en","type":"article","venue":"Language and Education","topic":"Second Language Learning and Teaching","field":"Arts and Humanities","cited_by":169,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ministerio de Educación, Cultura y Deporte; Eusko Jaurlaritza","keywords":"Multilingualism; Language policy; Competence (human resources); Multilingual Education; Computer science; Linguistics; Language industry; Context (archaeology); Language assessment; Sociology; Language education; Pedagogy; Comprehension approach; Psychology; Geography","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":[0.0001368287,0.0001020568,0.00009100889,0.0001363125,0.0001975962,0.0001435178,0.0000467879,0.00003280572,0.0007369255],"category_scores_gemma":[0.0001265741,0.00006977341,0.00001979833,0.00002321312,0.00007019856,0.0002055735,0.00002213629,0.00008342166,0.00002087642],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004120589,"about_ca_system_score_gemma":0.0002200076,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00477439,"about_ca_topic_score_gemma":0.0005834622,"domain_scores_codex":[0.9994317,0.00005106488,0.000112843,0.0001857365,0.00007317156,0.0001454558],"domain_scores_gemma":[0.9996184,0.00008043158,0.00005483642,0.0001372235,0.00003411834,0.00007500458],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.000002566166,0.00006315338,0.001030751,0.00002116555,0.000007847324,7.501196e-7,0.122174,2.08118e-8,0.001735052,0.02455306,0.0004636978,0.8499479],"study_design_scores_gemma":[0.0007604434,0.0001546167,0.01484534,0.0003183745,0.00006246866,0.00005493178,0.8281567,0.00002098645,0.001110697,0.0007593654,0.1532114,0.0005447667],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9530404,0.002371766,0.00001634399,0.001008926,0.0004097418,0.0000918651,0.00000674818,0.0000712217,0.04298296],"genre_scores_gemma":[0.9531962,0.00004193033,0.0002539981,0.0008333749,0.002091208,0.0000211714,0.00003087133,0.00001487705,0.04351637],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8494032,"threshold_uncertainty_score":0.8068817,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01137526861641941,"score_gpt":0.3113342774475442,"score_spread":0.2999590088311248,"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."}}