{"id":"W4396713321","doi":"10.2139/ssrn.4815300","title":"Submission to The Standing Committee on Industry and Technology on Bill C-27, An Act to enact the Consumer Privacy Protection Act, the Personal Information and Data Protection Tribunal Act and the Artificial Intelligence and Data Act and to make consequential and related amendments to other Acts","year":2024,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Ethics and Social Impacts of AI","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University; McMaster University","funders":"","keywords":"Dignity; Intersectionality; Argument (complex analysis); Inclusion (mineral); Data Protection Act 1998; Public domain; Personally identifiable information; Government (linguistics); Sociology; Political science; Subject (documents); Public policy; Law; Public relations; Internet privacy; Computer science","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":[0.009858985,0.0008996642,0.001526288,0.002126122,0.009501201,0.01223592,0.002581725,0.03948015,0.04275202],"category_scores_gemma":[0.03486593,0.001160035,0.002422363,0.00145824,0.003108531,0.002759149,0.00251671,0.02014291,0.03601826],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006635724,"about_ca_system_score_gemma":0.03550223,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04131073,"about_ca_topic_score_gemma":0.08581879,"domain_scores_codex":[0.9885828,0.001650898,0.0009039579,0.0008830704,0.005978684,0.002000441],"domain_scores_gemma":[0.9783539,0.008412044,0.0007016259,0.001385921,0.008803098,0.002343343],"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":[0.0000352468,0.00005981907,0.0002413653,0.00003534212,0.00001477004,0.00009114771,0.0001184577,0.00007547703,0.0003703973,0.03012334,0.9652354,0.003599261],"study_design_scores_gemma":[0.00005399238,0.00004540656,0.002398017,0.0002639347,0.00004407545,0.00005466156,0.0003763394,0.0003616197,0.0006013672,0.008099291,0.987632,0.00006937554],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.006576847,0.00209548,0.004109356,0.3015652,0.04460942,0.001544934,0.003086919,0.0009866668,0.6354252],"genre_scores_gemma":[0.01180835,0.0006619648,0.002109986,0.1941152,0.007134108,0.0007349328,0.00117053,0.0003501824,0.7819147],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9933643,"threshold_uncertainty_score":0.1430198,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1088018624428269,"score_gpt":0.3870339226049567,"score_spread":0.2782320601621298,"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."}}