{"id":"W4311955026","doi":"10.1007/s11162-022-09723-6","title":"Resetting Prices: Estimating the Effect of Tuition Reset Policies on Institutional Finances and Enrollment","year":2022,"lang":"en","type":"article","venue":"Research in Higher Education","topic":"Higher Education Research Studies","field":"Social Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Science Foundation","keywords":"Reset (finance); Attendance; Revenue; Economics; Higher education; Matriculation; Discounting; Monetary economics; Demographic economics; Actuarial science; Finance; Economic growth; Psychology; Mathematics 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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.009511192,0.00008522089,0.0001323782,0.0004937243,0.002754091,0.00009819312,0.0003869594,0.00003397652,0.000286577],"category_scores_gemma":[0.001201359,0.00006614971,0.0000266033,0.001610163,0.0008695872,0.0001856309,0.0002353728,0.0005476093,0.000007326921],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008166177,"about_ca_system_score_gemma":0.00112883,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005855048,"about_ca_topic_score_gemma":0.0001671704,"domain_scores_codex":[0.9946231,0.00265396,0.0002523148,0.0002688939,0.001754346,0.0004474369],"domain_scores_gemma":[0.9963111,0.003089319,0.0001028803,0.0002176703,0.0002050897,0.00007388344],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0003489052,0.0008969615,0.2965539,0.0005195131,0.00005595148,0.000004133478,0.07069542,0.003229005,0.0004094891,0.5427237,0.04284904,0.04171392],"study_design_scores_gemma":[0.0006738449,0.001138671,0.5386442,0.0003964826,0.000008621101,0.000001985843,0.02260893,0.0001736793,0.0003483399,0.01530428,0.4204576,0.0002433636],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9276227,0.001089711,0.00000193852,0.04242324,0.0006901119,0.001011347,0.00001184637,0.00001803755,0.02713112],"genre_scores_gemma":[0.995747,0.0001042586,0.0002384295,0.00007467355,0.0004850213,0.001456601,0.00001453237,0.00000699352,0.001872523],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5274194,"threshold_uncertainty_score":0.9985442,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1193378808255767,"score_gpt":0.5078352427282222,"score_spread":0.3884973619026455,"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."}}