{"id":"W2725254759","doi":"10.31235/osf.io/6cdhe","title":"Logics and practices of transparency and opacity in real-world applications of public sector machine learning","year":2017,"lang":"en","type":"preprint","venue":"","topic":"Regulation and Compliance Studies","field":"Business, Management and Accounting","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Transparency (behavior); Accountability; Public sector; Public relations; Nova scotia; Business; Political science; Computer science; Sociology; Computer security","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.03658945,0.0003177195,0.0003534517,0.001827965,0.007742462,0.01667003,0.001058262,0.003107971,0.003456551],"category_scores_gemma":[0.06546697,0.000621214,0.0003411846,0.003370769,0.03587335,0.01199778,0.007149369,0.00558535,0.0002580625],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01405293,"about_ca_system_score_gemma":0.01096207,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02756234,"about_ca_topic_score_gemma":0.02943582,"domain_scores_codex":[0.9489871,0.04085975,0.0013793,0.001949699,0.004789546,0.00203462],"domain_scores_gemma":[0.8988209,0.08444387,0.00634952,0.005574729,0.003750721,0.001060313],"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":[0.00006721346,0.0000305197,0.00564838,0.0001143305,0.00001420593,0.0004413088,0.1341685,0.0012266,0.0005628079,0.828971,0.003403898,0.02535125],"study_design_scores_gemma":[0.00004012465,0.00004696154,0.0107549,0.001064884,0.00003362652,0.0004937706,0.1169039,0.007821362,0.002935588,0.7003533,0.1594039,0.000147601],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.3941386,0.007392339,0.2312236,0.1371511,0.0004279882,0.0002711912,0.0003570615,0.0003497763,0.2286883],"genre_scores_gemma":[0.9900807,0.0006093351,0.006037736,0.0007020685,0.00004344283,0.00005296113,0.00003609584,0.0000516464,0.002386192],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9922575,"threshold_uncertainty_score":0.1935059,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1574278819720679,"score_gpt":0.3451709249132124,"score_spread":0.1877430429411445,"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."}}