{"id":"W4283165858","doi":"10.1177/19401612221106405","title":"How Climate Movement Actors and News Media Frame Climate Change and Strike: Evidence from Analyzing Twitter and News Media Discourse from 2018 to 2021","year":2022,"lang":"en","type":"article","venue":"The International Journal of Press/Politics","topic":"Climate Change Communication and Perception","field":"Social Sciences","cited_by":134,"is_retracted":false,"has_abstract":true,"ca_institutions":"MacEwan University","funders":"","keywords":"Framing (construction); Climate justice; Mainstream; Political science; Climate change; News media; Blame; Social media; Frame analysis; Politics; Social movement; Public relations; Political economy of climate change; Political economy; Sociology; Content analysis; Geography; Social science; Law; Social psychology","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":[0.0007589077,0.0001354639,0.0002082958,0.0001167856,0.0004609665,0.0005074415,0.0006510533,0.00005104653,0.0005077492],"category_scores_gemma":[0.0004241923,0.0001087543,0.00005442128,0.00007396868,0.0002344084,0.0005369472,0.0008150045,0.0003268417,0.000002236048],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000182068,"about_ca_system_score_gemma":0.00004314134,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008087723,"about_ca_topic_score_gemma":0.005907906,"domain_scores_codex":[0.9980242,0.0003783306,0.0003454566,0.0001796499,0.0008095177,0.0002627926],"domain_scores_gemma":[0.9978772,0.001117453,0.0003830026,0.0002073584,0.0001797476,0.0002351886],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0004289244,0.0002710028,0.1826628,0.00002932461,0.000478244,0.00005611157,0.6938423,0.0000524682,0.004719184,0.009783579,0.007700318,0.0999757],"study_design_scores_gemma":[0.002805031,0.0003468842,0.2821382,0.001311155,0.0006736287,0.00003045988,0.4873775,0.001507803,0.0003781573,0.03689239,0.1854483,0.001090519],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9267658,0.003050678,0.0001062983,0.06815149,0.001005227,0.0001664701,0.0006255255,0.000007816483,0.0001206825],"genre_scores_gemma":[0.9236116,0.07068553,0.0007045034,0.0026115,0.002258972,0.00001767355,0.00004849467,0.00001525659,0.00004647046],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2064648,"threshold_uncertainty_score":0.9985175,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3741404458652375,"score_gpt":0.4301319264093609,"score_spread":0.05599148054412334,"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."}}