{"id":"W4391614939","doi":"10.18260/1-2--42325","title":"“Just a little bit on the outside for the whole time”: Social belonging confidence and the persistence of machine learning and artificial intelligence students","year":2024,"lang":"en","type":"article","venue":"","topic":"Career Development and Diversity","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Mentorship; Field (mathematics); Persistence (discontinuity); Artificial intelligence; Computer science; Identity (music); Thematic analysis; Psychology; Mathematics education; Sociology; Qualitative research; Social science; Mathematics; Medical education","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":[],"consensus_categories":[],"category_scores_codex":[0.00416261,0.0001995321,0.0004458004,0.001326851,0.003906846,0.006861061,0.0006917211,0.001325177,0.004018798],"category_scores_gemma":[0.01821578,0.0002372201,0.0004336208,0.0007459619,0.004920696,0.003128812,0.004565212,0.003238366,0.0003733764],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001208452,"about_ca_system_score_gemma":0.001331004,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003827199,"about_ca_topic_score_gemma":0.004827941,"domain_scores_codex":[0.9971561,0.001345739,0.000136316,0.0002326772,0.0005289458,0.0006000993],"domain_scores_gemma":[0.9829144,0.005681826,0.004359838,0.0006535355,0.001534608,0.004855807],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001856125,0.001141936,0.5956979,0.0001116009,0.0001116326,0.0004359064,0.3612518,0.0001719983,0.001364639,0.005436365,0.001628707,0.03246187],"study_design_scores_gemma":[0.00001388675,0.0003412649,0.3945107,0.0001509444,0.00004360969,0.0003171854,0.5956341,0.0007742759,0.0004178172,0.003035706,0.004680029,0.00008059035],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9974274,0.00006573048,0.0001295701,0.0007385824,0.00001442631,0.000004965954,0.000007851801,0.000002878238,0.001608617],"genre_scores_gemma":[0.9995475,0.00003863688,0.00003644333,0.00008322478,0.000005951753,0.000004235586,0.000007886853,0.000002265577,0.0002737892],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006861061,"threshold_uncertainty_score":0.02201426,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06970317786342377,"score_gpt":0.3254367912616415,"score_spread":0.2557336133982178,"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."}}