{"id":"W2259626163","doi":"","title":"Media Literacy: Using a Game to Prompt Self-Reflection on Political Truth Biases","year":2015,"lang":"en","type":"article","venue":"Press Start (University of Glasgow)","topic":"Media Influence and Health","field":"Arts and Humanities","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"York University","keywords":"Politics; Media literacy; Reflection (computer programming); Literacy; Psychology; Political science; Sociology; Social psychology; Media studies; Computer science; Pedagogy; Law","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001542371,0.000115062,0.0002175202,0.0001703443,0.0001877841,0.00004686915,0.0001606382,0.0000474873,0.0003894731],"category_scores_gemma":[0.0001170178,0.0001220134,0.0000561785,0.00005006237,0.0001267283,0.0003916576,0.00006622362,0.0001232217,0.00009223192],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001405095,"about_ca_system_score_gemma":0.0001447499,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003881504,"about_ca_topic_score_gemma":0.001077282,"domain_scores_codex":[0.9989477,0.00006642962,0.000124288,0.0002149049,0.0003144281,0.0003322392],"domain_scores_gemma":[0.9989422,0.0001602831,0.00007294311,0.0001830078,0.0002534816,0.000388117],"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":[0.0008776491,0.0006699131,0.001212511,0.0002709948,0.0001072822,0.00005762722,0.4284424,0.0002361983,0.0001049698,0.5579467,0.008398809,0.001674885],"study_design_scores_gemma":[0.003089191,0.002197828,0.002422949,0.0008172932,0.0002721292,0.00001243094,0.06470256,0.007782273,0.0005480203,0.005921428,0.911361,0.0008729098],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9738687,0.0000432568,0.00006672768,0.0007422024,0.0004439074,0.0002317451,0.00007825428,0.0001011287,0.02442407],"genre_scores_gemma":[0.9976962,0.00001001118,0.0009847422,0.0003218073,0.0003925741,6.874503e-7,0.00001456919,0.00001053127,0.0005688645],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9029621,"threshold_uncertainty_score":0.5867699,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.226524218257031,"score_gpt":0.3138686368265395,"score_spread":0.08734441856950848,"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."}}