{"id":"W3007474103","doi":"10.22230/cjc.2020v45n1a3479","title":"Predictive Analytics and Child Welfare: Toward Data Justice","year":2020,"lang":"en","type":"article","venue":"Canadian Journal of Communication","topic":"Homelessness and Social Issues","field":"Health Professions","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Accountability; Deliberation; Analytics; Welfare; Predictive analytics; Transparency (behavior); Intervention (counseling); Public economics; Social Welfare; Economic Justice; Public relations; Business; Political science; Economics; Medicine; Data science; Computer science; Nursing; Law","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.1975876,0.0009868884,0.002354385,0.008685961,0.00566386,0.02575537,0.005736385,0.005707203,0.005283293],"category_scores_gemma":[0.4184515,0.001085609,0.00193636,0.01309371,0.02894094,0.02665786,0.01788291,0.0164178,0.001165266],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01113351,"about_ca_system_score_gemma":0.02863651,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01811137,"about_ca_topic_score_gemma":0.01007502,"domain_scores_codex":[0.8468832,0.1091897,0.007464393,0.008880317,0.02491367,0.002668774],"domain_scores_gemma":[0.3922675,0.4835915,0.01916488,0.05978836,0.04016448,0.005023271],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000242519,0.0001122698,0.01465694,0.001492772,0.0002904225,0.0002132427,0.007222682,0.006285908,0.0002976867,0.7435111,0.0485745,0.1770999],"study_design_scores_gemma":[0.00004754495,0.00004937103,0.002115823,0.003181104,0.0000695476,0.0001066396,0.004013113,0.01394548,0.0006696423,0.8773207,0.0984036,0.00007740968],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.01140459,0.02068729,0.4377363,0.4761897,0.002835372,0.0007235356,0.003208169,0.001901923,0.04531323],"genre_scores_gemma":[0.5242677,0.02331931,0.3781579,0.05346146,0.007579268,0.002048201,0.003607241,0.0009986537,0.006560155],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1975876,"threshold_uncertainty_score":0.9895173,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1548415563312477,"score_gpt":0.4074362224072909,"score_spread":0.2525946660760432,"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."}}