{"id":"W4393116790","doi":"10.1145/3613904.3642451","title":"\"This is not a data problem\": Algorithms and Power in Public Higher Education in Canada","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Ethics and Social Impacts of AI","field":"Social Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Automation; Power (physics); Sustainability; Qualitative property; Public relations; Algorithm; Political science; Machine learning; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001573727,0.0001588897,0.000243826,0.0001698342,0.0001146218,0.000718667,0.0006914357,0.0004094192,0.001704911],"category_scores_gemma":[0.0002518362,0.0001551103,0.00002135373,0.000318498,0.0001299269,0.0003109056,0.001343854,0.001210952,0.00001473279],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001186014,"about_ca_system_score_gemma":0.03876354,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9981856,"about_ca_topic_score_gemma":0.9986417,"domain_scores_codex":[0.9980282,0.000162279,0.0003020291,0.0005769746,0.0005580304,0.0003724858],"domain_scores_gemma":[0.9990112,0.0001312474,0.00007995538,0.0004219867,0.0001634115,0.0001922416],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000005263737,0.0001844371,0.01161423,0.0003122879,0.00007256241,0.00002730006,0.05016332,0.000001396894,0.000003086444,0.3411988,0.5495013,0.046916],"study_design_scores_gemma":[0.0001634471,0.000011669,0.01483853,0.0004131577,0.00001987796,3.356735e-7,0.007714622,0.0001813831,0.000002316379,0.2521483,0.7238773,0.0006291044],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.03027868,0.001227189,8.790173e-7,0.4151306,0.00250398,0.0006393156,0.0002036503,0.00003738199,0.5499783],"genre_scores_gemma":[0.9373776,0.0008948711,0.0006586417,0.007258113,0.0002845649,0.00003195035,0.00007766289,0.00002168274,0.05339488],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9070989,"threshold_uncertainty_score":0.9992077,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1145870908924796,"score_gpt":0.3947054580888054,"score_spread":0.2801183671963258,"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."}}