{"id":"W4387023330","doi":"10.24908/ss.v21i3.16105","title":"The “Academicon”: AI and Surveillance in Higher Education","year":2023,"lang":"en","type":"article","venue":"Surveillance & Society","topic":"Online Learning and Analytics","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Higher education; Reflection (computer programming); Focus (optics); Narrative; Sociology; Emerging technologies; Engineering ethics; Political science; Public relations; Data science; Computer science; Engineering; Artificial intelligence; Law","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.006737052,0.0006866133,0.0003605151,0.002644395,0.008939526,0.01367553,0.001392094,0.004849617,0.01081799],"category_scores_gemma":[0.01232953,0.0002850675,0.0004063133,0.00302265,0.02260595,0.01615632,0.0080485,0.006606006,0.001459919],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005348984,"about_ca_system_score_gemma":0.003942105,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00571014,"about_ca_topic_score_gemma":0.007555453,"domain_scores_codex":[0.9924861,0.005404937,0.0002062058,0.0004259087,0.001007785,0.0004690365],"domain_scores_gemma":[0.9877429,0.008211432,0.001025496,0.0004851122,0.001003513,0.001531524],"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":[0.00008284335,0.0001162785,0.00538656,0.000588677,0.00001627542,0.0005281012,0.1414484,0.0004969857,0.0007217514,0.6327825,0.07727777,0.140554],"study_design_scores_gemma":[0.000008491451,0.0001184152,0.003314902,0.001055517,0.000008524727,0.000582253,0.1036923,0.0005978349,0.0006921776,0.07201984,0.8178477,0.00006199012],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.05144967,0.05355161,0.03220242,0.4607695,0.009330751,0.000109527,0.0001538081,0.0003354358,0.3920972],"genre_scores_gemma":[0.8246249,0.0336199,0.009441502,0.06404331,0.008378856,0.0001626433,0.0001094366,0.0002320596,0.05938751],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9910605,"threshold_uncertainty_score":0.03880978,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01664618361590801,"score_gpt":0.2919202210740727,"score_spread":0.2752740374581646,"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."}}