{"id":"W4234952723","doi":"10.2196/preprints.32427","title":"The Plebeian Algorithm: A Democratic Approach to Censorship and Moderation (Preprint)","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University; Confederation College; Queen's University; Ontario Tech University","funders":"","keywords":"Social media; Misinformation; Computer science; False accusation; Preprint; Distrust; Moderation; Sanctions; Sentiment analysis; World Wide Web; Internet privacy; Algorithm; Political science; Computer security; Artificial intelligence; Law","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0381478,0.001023486,0.001911759,0.003932285,0.004491347,0.007144307,0.004089552,0.003428766,0.02256499],"category_scores_gemma":[0.1299922,0.0009997826,0.002515032,0.003699529,0.006186194,0.0105433,0.007673452,0.005091893,0.00378842],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003537024,"about_ca_system_score_gemma":0.004863218,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003234452,"about_ca_topic_score_gemma":0.005383207,"domain_scores_codex":[0.9677521,0.02497527,0.0009784842,0.002996484,0.002584075,0.0007134983],"domain_scores_gemma":[0.9164581,0.06664705,0.00316569,0.007192106,0.005421777,0.001115348],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003657298,0.0001778157,0.005320529,0.0002924385,0.0002103774,0.0001789432,0.002667576,0.03642733,0.000556742,0.7401879,0.01741385,0.1962007],"study_design_scores_gemma":[0.0001133378,0.0001091412,0.0009500145,0.0001362624,0.00006383709,0.0001139548,0.0008488363,0.3292437,0.0006614171,0.6413128,0.02638471,0.00006193867],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005944948,0.0001626991,0.9807118,0.00272739,0.0001928128,0.0005476398,0.0002695984,0.000542945,0.008900247],"genre_scores_gemma":[0.1356454,0.0002268648,0.848633,0.0007090407,0.0005070874,0.002309032,0.0005575864,0.0003405004,0.01107144],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0381478,"threshold_uncertainty_score":0.2017472,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04274086712065762,"score_gpt":0.3161583574404621,"score_spread":0.2734174903198044,"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."}}