{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001213421,0.0001157806,0.0001434483,0.00002594242,0.0002277889,0.0001607745,0.0004480518,0.00009117949,0.000003482636],"category_scores_gemma":[0.00007237429,0.00008878077,0.00006975025,0.0009224314,0.00009093596,0.0001425951,0.0001779352,0.000366062,0.00004272339],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004481736,"about_ca_system_score_gemma":0.0001328039,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004176415,"about_ca_topic_score_gemma":0.00006853226,"domain_scores_codex":[0.9987959,0.0001306228,0.0001967221,0.0003307731,0.0002020926,0.0003439425],"domain_scores_gemma":[0.9991138,0.0003314725,0.00007300363,0.0003575681,0.0000669105,0.00005723506],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000003376322,0.00003528463,0.8295137,0.00003474738,0.0000238732,0.000002165164,0.001425045,0.0003574444,0.0001546477,0.02918827,0.06956694,0.06969456],"study_design_scores_gemma":[0.0001948651,0.00001377067,0.8038445,0.00001296953,5.171016e-7,0.000002275833,0.0001585768,0.05069386,0.000004936348,0.006606717,0.1382807,0.0001863165],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6636327,0.006345295,0.001594777,0.3207375,0.003296067,0.0003686005,0.00001406595,0.001208846,0.002802199],"genre_scores_gemma":[0.9904675,0.002037771,0.0003924564,0.001380931,0.0002215483,0.00001166938,0.00000802501,0.00001093596,0.005469184],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3268348,"threshold_uncertainty_score":0.3620375,"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."}}