{"id":"W4205341406","doi":"10.1111/aspp.12621","title":"Education, language, and conflict in Myanmar's ethnic minority states","year":2022,"lang":"en","type":"article","venue":"Asian Politics & Policy","topic":"Asian Geopolitics and Ethnography","field":"Social Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"International Development Research Centre","keywords":"Ethnic group; Decentralization; State (computer science); Federalism; Democracy; Political science; Politics; Inclusion (mineral); Curriculum; Sociology; Public administration; Political economy; Gender studies; Law","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":[0.0006863948,0.00007835438,0.00009889362,0.0006712445,0.004416344,0.00185323,0.0002553675,0.000367192,0.002788502],"category_scores_gemma":[0.001622074,0.0001022222,0.00007058352,0.00103665,0.001647864,0.001022038,0.001831016,0.0007462875,0.0001163227],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001703949,"about_ca_system_score_gemma":0.001232907,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03793403,"about_ca_topic_score_gemma":0.0877832,"domain_scores_codex":[0.9995083,0.0002245342,0.00001787834,0.00002554816,0.0000256859,0.0001980654],"domain_scores_gemma":[0.9991419,0.0002748561,0.0003079059,0.00002359066,0.0000719674,0.0001797421],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.00006175291,0.000219893,0.4651092,0.00007724947,0.00002330694,0.0008801455,0.4959044,0.0001902365,0.0007747852,0.01707611,0.001662308,0.01802056],"study_design_scores_gemma":[0.000004110313,0.00004648695,0.272204,0.00009186747,0.000007173539,0.0001507195,0.7145878,0.0001402166,0.0002063345,0.001134629,0.01141363,0.0000130633],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9956157,0.0000879674,0.00001241258,0.0007311873,0.000002691751,0.000002091786,0.00001354714,4.170479e-7,0.003533874],"genre_scores_gemma":[0.9995828,0.00005412845,0.000007851108,0.00007325017,0.000001432594,0.000002839687,0.000005495214,2.721048e-7,0.0002719774],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03793403,"threshold_uncertainty_score":0.07542646,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01699192627169627,"score_gpt":0.3593886660155738,"score_spread":0.3423967397438776,"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."}}