{"id":"W4402722130","doi":"10.1145/3670947.3670976","title":"Beyond Predictive Algorithms in Child Welfare","year":2024,"lang":"en","type":"article","venue":"Graphics Interface","topic":"Ethics and Social Impacts of AI","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Welfare; Algorithm; Machine learning; Economics","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":[0.01771978,0.001393441,0.001064304,0.004247141,0.001167171,0.006144329,0.002428574,0.002013902,0.00452824],"category_scores_gemma":[0.08230846,0.0006723759,0.001034141,0.003457778,0.003111646,0.006039542,0.00337318,0.004146915,0.0008319811],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003249464,"about_ca_system_score_gemma":0.002884756,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01037805,"about_ca_topic_score_gemma":0.008151736,"domain_scores_codex":[0.990252,0.006763656,0.0004361161,0.001112334,0.001143271,0.000292615],"domain_scores_gemma":[0.9203137,0.06947291,0.00313498,0.003400698,0.003083929,0.0005937787],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002720296,0.0003120685,0.0321678,0.0005337092,0.000280374,0.0002205433,0.003012339,0.5347529,0.0006402995,0.1137075,0.00545828,0.3086422],"study_design_scores_gemma":[0.00002505357,0.00004775409,0.001809046,0.0002193623,0.00002605746,0.0000402548,0.0006120584,0.8069274,0.0005418655,0.1853881,0.004331849,0.00003116665],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07421245,0.001863409,0.9038923,0.006768071,0.0001624648,0.0004183894,0.0005396339,0.001689959,0.01045339],"genre_scores_gemma":[0.6640902,0.001045678,0.3297128,0.001004244,0.0002303741,0.0005685166,0.001025453,0.0001975471,0.002125197],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01771978,"threshold_uncertainty_score":0.09371233,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02271322520061152,"score_gpt":0.3559928765445183,"score_spread":0.3332796513439067,"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."}}