{"id":"W4323544814","doi":"10.1177/17504813231156748","title":"A corpus-assisted discourse analysis of the representation of Syrian refugees in Canadian newspapers","year":2023,"lang":"en","type":"article","venue":"Discourse & Communication","topic":"Hate Speech and Cyberbullying Detection","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Refugee; Newspaper; Critical discourse analysis; Ideology; Representation (politics); Immigration; Discourse analysis; Politics; Syrian refugees; Sociology; Corpus linguistics; Media studies; Gender studies; Political science; Linguistics; Law","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002942361,0.000546954,0.0003843716,0.01615952,0.008700944,0.004309772,0.0008688006,0.0005416552,0.003564546],"category_scores_gemma":[0.009522945,0.0002647238,0.000212972,0.0197945,0.003777742,0.001220528,0.002075419,0.0008314934,0.0003686679],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02511525,"about_ca_system_score_gemma":0.03758934,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8886711,"about_ca_topic_score_gemma":0.934568,"domain_scores_codex":[0.9981951,0.0004237684,0.00009699781,0.0002776383,0.0006755507,0.0003309322],"domain_scores_gemma":[0.9890515,0.004431748,0.0008661864,0.0004199694,0.004710137,0.0005203159],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002507878,0.00008851094,0.03295811,0.0008995722,0.00002616523,0.001396307,0.8424826,0.0002406752,0.01281445,0.006575712,0.01177259,0.09049448],"study_design_scores_gemma":[0.0000168171,0.00004811817,0.1427694,0.0005255294,0.00006678394,0.0003475638,0.6657804,0.0009371201,0.004592546,0.000552913,0.1842682,0.00009458621],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9513287,0.001530783,0.002355083,0.001383568,0.0001307928,0.0005049657,0.01134115,0.0001264384,0.03129858],"genre_scores_gemma":[0.9687389,0.002074009,0.01004276,0.0002466345,0.00007331088,0.0004717965,0.006938645,0.00009995812,0.01131405],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1113289,"threshold_uncertainty_score":0.223969,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02181606312837562,"score_gpt":0.3211826949450325,"score_spread":0.2993666318166569,"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."}}