{"id":"W4386331843","doi":"10.32920/24065577","title":"Election success and voter privacy: a delicate equilibrium","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Legal and Policy Issues","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Modernization theory; Ballot; Enforcement; Public administration; Politics; Political science; Privacy policy; Accountability; FTC Fair Information Practice; Personally identifiable information; Business; Law and economics; Information privacy; Information privacy law; Law; Economics; Voting","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":[0.0003793575,0.0001328736,0.0001763205,0.00008754304,0.000169158,0.0003394107,0.000294442,0.0002653045,0.0001456534],"category_scores_gemma":[0.0001215693,0.0001133559,0.00005917746,0.0001630388,0.0001468225,0.0001296699,0.0005795662,0.000277914,0.000203887],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005335006,"about_ca_system_score_gemma":0.0001693169,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1171296,"about_ca_topic_score_gemma":0.0116112,"domain_scores_codex":[0.9988358,0.0001184683,0.0001579793,0.0003390399,0.0002355155,0.0003131773],"domain_scores_gemma":[0.9994724,0.00007139792,0.0000675111,0.0001966505,0.00006911721,0.0001229085],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001375389,0.000220721,0.07224416,0.001148192,0.0005544666,0.00005013972,0.2682807,0.00009398878,0.002067611,0.2331741,0.3821568,0.03987165],"study_design_scores_gemma":[0.0001711608,0.00003504092,0.01175994,0.00008735965,0.00005403137,0.000001210895,0.0004309786,0.0003225003,0.001163712,0.1456056,0.8397718,0.0005966107],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7218806,0.000231585,0.0001998924,0.09406826,0.001548702,0.0006180655,0.00002100181,0.001108012,0.1803239],"genre_scores_gemma":[0.9206625,0.0003418083,0.0001367067,0.0004975938,0.001239452,0.00003966729,0.00001282684,0.00001882725,0.07705066],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.457615,"threshold_uncertainty_score":0.8887495,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08694357494512778,"score_gpt":0.3948818155204432,"score_spread":0.3079382405753154,"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."}}