{"id":"W3196817970","doi":"10.33137/ijidi.v5i3.36159","title":"Promoting Linguistic Diversity and Inclusion","year":2021,"lang":"en","type":"article","venue":"The International Journal of Information Diversity & Inclusion (IJIDI)","topic":"Wikis in Education and Collaboration","field":"Social Sciences","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Machine translation; Literacy; Diversity (politics); Computer science; Information literacy; Inclusion (mineral); Artificial intelligence; Mathematics education; Pedagogy; World Wide Web; Sociology; Psychology; Social science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0249106,0.0004996303,0.0007452513,0.004351591,0.02276473,0.01532403,0.002369739,0.003299164,0.0135732],"category_scores_gemma":[0.04146867,0.0003983921,0.0007412967,0.002366876,0.01018385,0.01265973,0.04472944,0.00457979,0.002852948],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006676922,"about_ca_system_score_gemma":0.02353112,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01189466,"about_ca_topic_score_gemma":0.01864555,"domain_scores_codex":[0.9737716,0.01401846,0.001046281,0.001643387,0.005494159,0.004026165],"domain_scores_gemma":[0.9603021,0.01270728,0.003494654,0.003965725,0.008305689,0.01122469],"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":[0.0001035588,0.000476662,0.01634528,0.0007093484,0.00004388505,0.001987496,0.4611043,0.0002057184,0.004321648,0.1756949,0.05368263,0.2853245],"study_design_scores_gemma":[0.00003833263,0.0001387016,0.01178805,0.001246203,0.00002837388,0.001249769,0.1317578,0.0002322247,0.001150931,0.04978752,0.8024969,0.00008529882],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.186404,0.004042397,0.01863797,0.1339012,0.001553073,0.0006466404,0.000185927,0.0003905791,0.6542382],"genre_scores_gemma":[0.9047444,0.00171933,0.01455163,0.01640916,0.0006356536,0.000639171,0.0001610347,0.0002239731,0.0609155],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0249106,"threshold_uncertainty_score":0.1317414,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0170181528171583,"score_gpt":0.2918290807704478,"score_spread":0.2748109279532895,"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."}}