{"id":"W3133596884","doi":"10.3138/cpp.2020-109","title":"Predicted Earnings Losses from Graduating during COVID-19","year":2021,"lang":"en","type":"article","venue":"Canadian Public Policy","topic":"Employment and Welfare Studies","field":"Health Professions","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Statistics Canada; Memorial University of Newfoundland","funders":"","keywords":"Earnings; Graduation (instrument); Unemployment; Demographic economics; Coronavirus disease 2019 (COVID-19); Recession; Population; Cohort; Political science; Demography; Economics; Humanities; Sociology; Art; Economic growth; Medicine; Accounting; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"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":[0.0007499409,0.0004149217,0.0002266929,0.00102199,0.0007084625,0.0008839757,0.0005657457,0.0007104476,0.004774212],"category_scores_gemma":[0.002847034,0.0001800455,0.0004792735,0.00052771,0.0002387708,0.0003716342,0.0009478647,0.0009525588,0.00200559],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00234446,"about_ca_system_score_gemma":0.001765234,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2573802,"about_ca_topic_score_gemma":0.3163682,"domain_scores_codex":[0.9996562,0.00002456378,0.00001491117,0.0000396859,0.00009744896,0.0001671601],"domain_scores_gemma":[0.9983464,0.0001434778,0.0003874772,0.00003787954,0.0004017251,0.0006829987],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001046823,0.0001126547,0.9748508,0.00001682958,0.00002116586,0.0001061675,0.0001389393,0.007432583,0.0001282912,0.0006382161,0.00698099,0.009468566],"study_design_scores_gemma":[0.0000119319,0.0001076896,0.9762635,0.00004763998,0.00001810738,0.00006453974,0.0006049147,0.01817164,0.0001862306,0.0004900155,0.004017981,0.00001591015],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9758679,0.0002678828,0.0006550232,0.001903134,0.00007463429,0.00004840732,0.01439347,0.00006455433,0.006724962],"genre_scores_gemma":[0.9830939,0.0002517346,0.0002817853,0.0001440421,0.00003534988,0.00002433267,0.0110401,0.000006838465,0.00512192],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7426198,"threshold_uncertainty_score":0.5117643,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08241746083482708,"score_gpt":0.3972087141660523,"score_spread":0.3147912533312252,"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."}}