{"id":"W3164487350","doi":"10.3968/12017","title":"Innovation of Ideological and Political Education in Big Data Age","year":2021,"lang":"en","type":"article","venue":"Canadian social science","topic":"Ideological and Political Education","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Ideology; Big data; Subjectivity; Politics; Political education; Quality (philosophy); Public relations; Sociology; Political science; Social science; Epistemology; Computer science; Law; Data mining","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":[0.01584366,0.0003171473,0.0004912608,0.00414055,0.004974359,0.01054818,0.001450998,0.00149551,0.007734912],"category_scores_gemma":[0.0246702,0.0002723877,0.00067099,0.004618408,0.01214064,0.01145194,0.005193249,0.005032153,0.001283855],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007857286,"about_ca_system_score_gemma":0.02677777,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0196067,"about_ca_topic_score_gemma":0.02665616,"domain_scores_codex":[0.9911384,0.003132819,0.0003176546,0.0006762324,0.003637552,0.001097203],"domain_scores_gemma":[0.9739634,0.01152171,0.001313516,0.002818518,0.006312666,0.004070159],"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":[0.00003513222,0.0001055517,0.009946727,0.0004007103,0.00002386012,0.0001771837,0.01921244,0.0003522881,0.0004510036,0.6987357,0.07694315,0.1936163],"study_design_scores_gemma":[0.00001631549,0.00002219871,0.009414581,0.0004644649,0.000009984706,0.0001368242,0.01656218,0.001193687,0.0006067367,0.285316,0.6862125,0.00004446308],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.09349049,0.01590551,0.05462589,0.4305715,0.009585772,0.000267244,0.001407155,0.0005968619,0.3935496],"genre_scores_gemma":[0.8347243,0.01640379,0.05188667,0.02664999,0.005413007,0.0002429113,0.001107503,0.0004209268,0.06315086],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0196067,"threshold_uncertainty_score":0.0837903,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1179979981614594,"score_gpt":0.4009791262051151,"score_spread":0.2829811280436557,"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."}}