{"id":"W3199819681","doi":"10.32920/22227871.v1","title":"Privacy by Design by Regulation: The Case Study of Ontario","year":2023,"lang":"en","type":"article","venue":"","topic":"Cybercrime and Law Enforcement Studies","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Tel Aviv University","keywords":"Commission; Privacy by Design; Information privacy; Regulator; Privacy policy; European commission; Business; General Data Protection Regulation; Internet privacy; European union; Legal aspects of computing; FTC Fair Information Practice; Information privacy law; Privacy law; Data Protection Act 1998; Public relations; Political science; Public administration; Law; Computer science; The Internet","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":[0.0002768917,0.00006782784,0.00008490265,0.00002102999,0.0002101678,0.00004019828,0.0003460937,0.00001189795,0.00006681876],"category_scores_gemma":[0.000007352245,0.00004165047,0.0000207736,0.0002969664,0.00001918429,0.0001450469,0.0003050435,0.00004074765,0.00002786018],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003599194,"about_ca_system_score_gemma":0.00003736362,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08143725,"about_ca_topic_score_gemma":0.01616818,"domain_scores_codex":[0.9993466,0.00004472656,0.0001598361,0.0001604141,0.0001678295,0.000120612],"domain_scores_gemma":[0.9993908,0.0001108556,0.00003479095,0.0004118051,0.00003238539,0.00001933979],"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":[0.000005249109,0.0002397235,0.002487727,0.000003577142,0.00009784349,0.00009249207,0.05461485,0.0002935557,0.0002533413,0.007201639,0.9268143,0.007895726],"study_design_scores_gemma":[0.008487118,0.005722307,0.05176774,0.00004358482,0.0002554317,0.0005290572,0.05009475,0.06506991,0.02443123,0.007679875,0.7839277,0.001991216],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8623095,0.00004304786,0.1275412,0.0009508745,0.0001345805,0.0006342674,7.09113e-7,0.0001856591,0.008200186],"genre_scores_gemma":[0.9733077,0.000001985968,0.0005196267,0.0001013264,0.00000733672,0.00002089167,0.000001057103,0.000002647709,0.0260374],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1428865,"threshold_uncertainty_score":0.9246795,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05430984086848874,"score_gpt":0.277206987178506,"score_spread":0.2228971463100173,"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."}}