{"id":"W2579899860","doi":"10.1017/s0047404516001020","title":"Controlling Roma refugees with ‘Google-Hungarian’: Indexing deviance, contempt, and belonging in Toronto's linguistic landscape","year":2017,"lang":"en","type":"article","venue":"Language in Society","topic":"Romani and Gypsy Studies","field":"Health Professions","cited_by":85,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Indexicality; Linguistic landscape; Signage; Sociology; Multilingualism; Ethnography; Face (sociological concept); Linguistics; Anthropology; Social science; Visual arts","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007293731,0.0001946541,0.0004642327,0.00002237624,0.001083983,0.00005028459,0.0001982909,0.0001857354,0.00004819783],"category_scores_gemma":[0.0005094348,0.0001553875,0.00005233735,0.00005244697,0.000100971,0.0001971286,0.0001591927,0.0005519433,0.000004789203],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001980405,"about_ca_system_score_gemma":0.00007435269,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01109713,"about_ca_topic_score_gemma":0.1039436,"domain_scores_codex":[0.9984735,0.0001209133,0.0003745805,0.0003348189,0.0001601025,0.0005360753],"domain_scores_gemma":[0.9987486,0.00049406,0.0002606766,0.0003686696,0.0000586078,0.00006940308],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007831713,0.00003006278,0.9119852,0.0002164249,0.00005948771,0.000105355,0.08474163,0.000006214045,0.0001440168,0.00100927,0.000246261,0.001377742],"study_design_scores_gemma":[0.006189718,0.00007900638,0.9052058,0.002143702,0.00003398665,0.000003750483,0.08060218,0.002147248,0.00002064023,0.0001459084,0.003035955,0.0003920809],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.962217,0.007580967,0.0000617154,0.0003933103,0.000255864,0.0005024694,0.00001066254,0.00006132285,0.02891668],"genre_scores_gemma":[0.9966986,0.0002322522,0.0009898905,0.0005325652,0.0003654373,0.00008845679,0.000005485816,0.00002780297,0.001059512],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09284645,"threshold_uncertainty_score":0.995488,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01894836310804459,"score_gpt":0.3861514127513312,"score_spread":0.3672030496432866,"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."}}