{"id":"W4312694957","doi":"10.2139/ssrn.4226330","title":"Privacy Dark Patterns: A Case for Regulatory Reform in Canada","year":2022,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Legal Systems and Judicial Processes","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Personally identifiable information; Internet privacy; Privacy policy; Information privacy; Business; Information privacy law; Privacy by Design; Legislature; Privacy law; Population; CLARITY; Privacy laws of the United States; The Internet; Political science; Law; Sociology; Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008746054,0.0002376908,0.0008036834,0.002597793,0.03709696,0.01530613,0.003423822,0.007895573,0.01044228],"category_scores_gemma":[0.03630106,0.0005881288,0.0007587586,0.005670771,0.01380677,0.004059552,0.004764558,0.01250557,0.0003703008],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.1433891,"about_ca_system_score_gemma":0.3058929,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9934689,"about_ca_topic_score_gemma":0.9965962,"domain_scores_codex":[0.9863237,0.001620305,0.0003150266,0.001186821,0.003685235,0.006868887],"domain_scores_gemma":[0.9719661,0.007231459,0.001953072,0.001549354,0.01079003,0.006509925],"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":[0.0002775747,0.0001798679,0.06374893,0.0001319637,0.000109284,0.001571156,0.05580474,0.002647726,0.001316027,0.7432584,0.08023749,0.05071685],"study_design_scores_gemma":[0.00038137,0.0001317689,0.1716472,0.0007151928,0.0002767062,0.0005355571,0.1949907,0.00866275,0.002354744,0.1814695,0.4382145,0.0006200192],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5673058,0.001345219,0.004024828,0.2671328,0.0003734781,0.0002482529,0.0008027221,0.0001067724,0.1586601],"genre_scores_gemma":[0.9643851,0.0003506061,0.001100542,0.01715994,0.00004220505,0.00003196124,0.00008838072,0.00004337142,0.01679789],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1433891,"threshold_uncertainty_score":0.9935473,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01113064887425854,"score_gpt":0.2589401343547555,"score_spread":0.247809485480497,"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."}}