{"id":"W4396936132","doi":"10.1007/s00146-024-01952-w","title":"Deconstructing public participation in the governance of facial recognition technologies in Canada","year":2024,"lang":"en","type":"article","venue":"AI & Society","topic":"Ethics and Social Impacts of AI","field":"Social Sciences","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"Social Sciences and Humanities Research Council","keywords":"Performing arts; Corporate governance; Political science; Business; Sociology; Public relations; Visual arts; Art","routes":{"ca_aff":true,"ca_fund":true,"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":["sts"],"consensus_categories":[],"category_scores_codex":[0.01333968,0.0003543712,0.0004799428,0.002007905,0.02756674,0.01977411,0.003210625,0.00469285,0.006357688],"category_scores_gemma":[0.03135824,0.0005664965,0.0005160357,0.002487452,0.02398979,0.003337871,0.007281546,0.006571741,0.0003690071],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.2353031,"about_ca_system_score_gemma":0.3543425,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.993525,"about_ca_topic_score_gemma":0.995188,"domain_scores_codex":[0.9800964,0.004805173,0.0003905367,0.001545537,0.005087088,0.008075264],"domain_scores_gemma":[0.9731265,0.009595829,0.00151809,0.001442874,0.01001008,0.004306682],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.00012327,0.0001276791,0.03334049,0.00009341773,0.00006944282,0.0006612595,0.113069,0.005468963,0.001086157,0.7820754,0.01934496,0.04454005],"study_design_scores_gemma":[0.0001011638,0.0001093758,0.08945902,0.0005367078,0.0001856021,0.000206878,0.3322243,0.01857503,0.002387423,0.1599316,0.3959295,0.0003535317],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5474347,0.0009291273,0.007285709,0.07409272,0.0001789066,0.000238226,0.0002424465,0.00008164192,0.3695164],"genre_scores_gemma":[0.9888999,0.0001599965,0.0004798967,0.001043153,0.00001294301,0.00002210417,0.00002186195,0.00001744294,0.009342566],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9724333,"threshold_uncertainty_score":0.88694,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06256826352557678,"score_gpt":0.3568508307745601,"score_spread":0.2942825672489833,"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."}}