{"id":"W4394844338","doi":"10.2139/ssrn.4783525","title":"Perceptions of Canada’s AI Governance System: Findings from Interviews with 20 Government Leaders & Subject Matter Experts","year":2024,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Legal and Policy Issues","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Subject (documents); Subject matter; Corporate governance; Perception; Government (linguistics); Political science; Public administration; Psychology; Public relations; Management; Law; Economics; Philosophy; Computer science; Library 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":[0.006767382,0.0002432424,0.0002514988,0.002149988,0.02238393,0.008565746,0.001337714,0.001752716,0.004175561],"category_scores_gemma":[0.01699149,0.000356282,0.0001687332,0.003309768,0.008085094,0.001945349,0.002450761,0.003438367,0.0002135432],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.09017672,"about_ca_system_score_gemma":0.1442226,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9839931,"about_ca_topic_score_gemma":0.9900866,"domain_scores_codex":[0.991982,0.001927613,0.000226658,0.0004726144,0.001998268,0.003392769],"domain_scores_gemma":[0.9714401,0.007979543,0.002197239,0.0002741856,0.009075842,0.009033056],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00008691977,0.0000976845,0.06444413,0.00009928679,0.0000175908,0.0005678372,0.9001781,0.0002449045,0.001235282,0.009072373,0.01070529,0.01325069],"study_design_scores_gemma":[0.000008609587,0.0000299661,0.05526662,0.0001160973,0.000008579989,0.00005126178,0.8855689,0.0002816866,0.0003075704,0.0004232729,0.05789902,0.00003843946],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9276191,0.0004709371,0.0004978019,0.01429117,0.00006445497,0.0001136658,0.0002688422,0.0000146914,0.05665929],"genre_scores_gemma":[0.9929566,0.000240674,0.0001887957,0.001585622,0.000009645265,0.00002417382,0.00006162191,0.000008228895,0.004924657],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9098233,"threshold_uncertainty_score":0.6542809,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01669133294360938,"score_gpt":0.2900663357303495,"score_spread":0.2733750027867401,"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."}}