{"id":"W4398183460","doi":"10.5539/ijel.v14n3p42","title":"A Corpus-Based Critical Discourse Analysis of Chinese and American News Coverage on Climate Change","year":2024,"lang":"en","type":"article","venue":"International Journal of English Linguistics","topic":"Climate Change Communication and Perception","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Critical discourse analysis; Climate change; Political science; Linguistics; Psychology; Geology; Law; Philosophy; Oceanography; Politics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002854117,0.0003744576,0.0003083293,0.01054535,0.004020599,0.001858223,0.0004376336,0.0004409504,0.002318852],"category_scores_gemma":[0.009553333,0.0001498275,0.000205754,0.01450569,0.002031644,0.001618626,0.001311008,0.0006788937,0.0001882648],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004306665,"about_ca_system_score_gemma":0.004508066,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03556763,"about_ca_topic_score_gemma":0.04044548,"domain_scores_codex":[0.9989485,0.000432543,0.00009611447,0.0001608224,0.0002416387,0.0001203996],"domain_scores_gemma":[0.9849573,0.01118157,0.0009734858,0.0004126598,0.002145805,0.00032918],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0003622539,0.0002592655,0.06380006,0.001330029,0.00003895673,0.002004687,0.8101431,0.0002805325,0.01053425,0.01250976,0.007896052,0.09084103],"study_design_scores_gemma":[0.00004617765,0.0001705974,0.3148982,0.0005775822,0.0001507925,0.0006994486,0.5648004,0.004518838,0.009478148,0.002549413,0.1020135,0.00009690339],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9797161,0.0005965646,0.001730482,0.0006778308,0.00009137749,0.0002757435,0.002357601,0.00003441639,0.0145201],"genre_scores_gemma":[0.9882808,0.0006287951,0.003737265,0.0001143412,0.00008683485,0.0005966891,0.002885895,0.00002849562,0.003640841],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03556763,"threshold_uncertainty_score":0.07072121,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1488981791014655,"score_gpt":0.4819759555124243,"score_spread":0.3330777764109588,"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."}}