{"id":"W4285232790","doi":"10.2139/ssrn.4139639","title":"It Shouldn’t be Small Potatoes: The Future of Civil Damage Awards under Canada’s Personal Information Protection Legislation. Part Two: Inadequate PIPEDA Damages and the Way Forward","year":2022,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Criminal Law and Evidence","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University; University of Alberta","funders":"","keywords":"Damages; Legislation; Personally identifiable information; Business; Law; Personal injury; Political 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":[0.01282229,0.0003128302,0.0004958367,0.002560966,0.01014513,0.01643615,0.002373071,0.008881504,0.01486762],"category_scores_gemma":[0.04989476,0.000484673,0.0005248159,0.002964064,0.01064012,0.006737136,0.003102546,0.008483839,0.001134059],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.080968,"about_ca_system_score_gemma":0.1849736,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.958478,"about_ca_topic_score_gemma":0.9826035,"domain_scores_codex":[0.9859832,0.001741449,0.0003271447,0.0006627346,0.00660905,0.004676481],"domain_scores_gemma":[0.9577798,0.01447461,0.002312495,0.001264184,0.01912631,0.005042489],"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":[0.0001462524,0.00008792608,0.02778546,0.0001973663,0.00005261378,0.0002647946,0.00613137,0.001298463,0.000298704,0.4646322,0.4271543,0.07195058],"study_design_scores_gemma":[0.0001367452,0.0001317604,0.1485971,0.00218869,0.0002481724,0.0002673727,0.02217468,0.00343091,0.001433957,0.1221194,0.6988692,0.0004020777],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.06706025,0.01268267,0.001068111,0.7102383,0.00110428,0.00009637578,0.001603223,0.00005766419,0.2060892],"genre_scores_gemma":[0.8537254,0.009770657,0.001219163,0.0559431,0.0008907856,0.00006655505,0.000482902,0.0000721388,0.07782919],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.080968,"threshold_uncertainty_score":0.5874667,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01937012400088212,"score_gpt":0.2605029007190654,"score_spread":0.2411327767181833,"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."}}