{"id":"W4205515629","doi":"10.31124/advance.14770296.v1","title":"The construction of the Covid-19 pandemic as a social problem: expert discourse and representational naturalization in the mass media during the first wave of the pandemic in Canada","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Social Representations and Identity","field":"Psychology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Naturalization; Appropriation; Context (archaeology); Pandemic; Relevance (law); Mass media; Politics; Sociology; Political science; Discourse analysis; Social media; Coronavirus disease 2019 (COVID-19); Public relations; Media studies; Social science; Epistemology; Law; Linguistics; History; Medicine; Citizenship","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":[0.0008011315,0.0001763906,0.0002482398,0.00004804405,0.0006123283,0.00008182992,0.0006198502,0.0002012556,0.0001397452],"category_scores_gemma":[0.0007617751,0.00007971119,0.0001380299,0.0004789362,0.000752885,0.00007070406,0.0004063622,0.0007429874,2.150284e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005316493,"about_ca_system_score_gemma":0.001683713,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8016651,"about_ca_topic_score_gemma":0.9625878,"domain_scores_codex":[0.9969806,0.001157336,0.0006378965,0.0003583456,0.000650192,0.0002156194],"domain_scores_gemma":[0.9973742,0.001325316,0.0005832182,0.0005555286,0.0001353392,0.00002643695],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000058419,0.00002988496,0.9388683,0.00005071079,0.000100249,0.00000275777,0.05090106,0.000309796,0.00009354475,0.007974551,0.001156149,0.0004545674],"study_design_scores_gemma":[0.0005677553,0.000002396587,0.853465,0.00004283783,0.00003637967,0.00003869538,0.1342528,0.00008988351,0.00003166791,0.01119337,0.0001785452,0.0001007429],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9825832,0.0005497221,0.00003872612,0.01330396,0.001261901,0.00114884,0.00004726927,0.00000737797,0.001059039],"genre_scores_gemma":[0.9983798,0.0004562593,0.00001513464,0.0004773088,0.0001449427,0.0002806551,0.00002553518,0.00001204113,0.0002083739],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1609226,"threshold_uncertainty_score":0.4709596,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04576190556468272,"score_gpt":0.3642728776083677,"score_spread":0.318510972043685,"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."}}