{"id":"W2736467424","doi":"10.1093/acrefore/9780199384655.013.230","title":"Linguistic Landscape of Ethiopia","year":2017,"lang":"en","type":"reference-entry","venue":"Oxford Research Encyclopedia of Linguistics","topic":"Multilingual Education and Policy","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Linguistic landscape; Linguistics; Language policy; Multilingualism; Sociolinguistics; Scholarship; Sociology; Politics; Context (archaeology); Federalism; Linguistic demography; Political science; Sociology of language; Social science; Geography; Language education; 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":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.003952208,0.000326936,0.0008962908,0.0007918623,0.0008865521,0.0001160595,0.001956296,0.001023836,0.0008788504],"category_scores_gemma":[0.1975121,0.0003195855,0.0002512002,0.0004570105,0.001810928,0.00002497607,0.0003391647,0.002040758,0.00004561806],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001578852,"about_ca_system_score_gemma":0.01121816,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009337322,"about_ca_topic_score_gemma":0.002041043,"domain_scores_codex":[0.9943418,0.0007965223,0.000970004,0.0005065199,0.002383585,0.001001549],"domain_scores_gemma":[0.9878482,0.003019852,0.0009813927,0.001207641,0.006413138,0.000529747],"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":[0.0001373093,0.0007737832,0.006639086,0.004965414,0.0002430081,0.00005254531,0.08921298,0.000003596632,3.964548e-7,0.1854137,0.4645514,0.2480068],"study_design_scores_gemma":[0.0002259724,0.0001034523,0.0002265734,0.001035315,0.0000606351,2.905096e-7,0.001275934,0.00001169489,0.00000528182,0.004433072,0.9923434,0.0002783335],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"review","genre_scores_codex":[0.0002916806,0.003254551,0.000006073828,0.0001766243,0.008462524,0.0005489893,0.0004216199,0.00003807926,0.9867998],"genre_scores_gemma":[0.01320573,0.5183395,0.001122496,0.00001939158,0.01794669,0.00002777319,0.0002151571,0.00006342729,0.4490598],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.53774,"threshold_uncertainty_score":0.9999256,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1650944983007979,"score_gpt":0.5127016026587784,"score_spread":0.3476071043579805,"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."}}