{"id":"W4389249219","doi":"10.1017/s0047404523000659","title":"From punitive multilingualism and forensic translation towards linguistic justice","year":2023,"lang":"en","type":"article","venue":"Language in Society","topic":"Interpreting and Communication in Healthcare","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Punitive damages; Multilingualism; Content (measure theory); Linguistics; Economic Justice; Action (physics); Sociology; Political science; Law; Mathematics; Philosophy","routes":{"ca_aff":true,"ca_fund":false,"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":[0.006327468,0.0006067939,0.0004315184,0.001105584,0.004907792,0.01081293,0.0009088914,0.002128792,0.01504479],"category_scores_gemma":[0.02290131,0.0003270585,0.0003282962,0.0009511802,0.02027923,0.008447228,0.01134882,0.004972729,0.003171692],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003391967,"about_ca_system_score_gemma":0.005140899,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003199882,"about_ca_topic_score_gemma":0.004442722,"domain_scores_codex":[0.9907709,0.006445688,0.0004323763,0.0005225797,0.001202445,0.0006258551],"domain_scores_gemma":[0.9883885,0.005496026,0.001042616,0.002707608,0.0017777,0.0005874973],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007249091,0.00003602578,0.0007328769,0.0001665551,0.00001225945,0.0006636353,0.04397923,0.0001912927,0.0004744371,0.9047507,0.01513989,0.03378052],"study_design_scores_gemma":[0.00002803737,0.00004860796,0.001171312,0.000881536,0.00002098116,0.001121294,0.05446778,0.0009103721,0.002536898,0.7469691,0.1917897,0.000054349],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.05186094,0.003057596,0.03304752,0.06182889,0.002163284,0.00006208314,0.0001532618,0.000303251,0.8475232],"genre_scores_gemma":[0.9593482,0.001519131,0.005940562,0.003731516,0.0004586152,0.00004875482,0.0001024461,0.0002987202,0.02855214],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01504479,"threshold_uncertainty_score":0.0503298,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09995797287226339,"score_gpt":0.47965861411661,"score_spread":0.3797006412443466,"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."}}