{"id":"W2522846443","doi":"10.1017/asb.2016.20","title":"HOW ACCURATELY DOES 70% FINAL EMPLOYMENT EARNINGS REPLACEMENT MEASURE RETIREMENT INCOME (IN)ADEQUACY? INTRODUCING THE LIVING STANDARDS REPLACEMENT RATE (LSRR)","year":2016,"lang":"en","type":"article","venue":"Astin Bulletin","topic":"demographic modeling and climate adaptation","field":"Decision Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Statistics Canada; Dalhousie University; University of Prince Edward Island","funders":"Rotman School of Management, University of Toronto; Dalhousie University; Towson University; University of Toronto; Society of Actuaries","keywords":"Earnings; Standard of living; Economics; Population; Retirement age; Demographic economics; Labour economics; Actuarial science; Pension; Finance; Demography","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"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":[0.005692856,0.0002898868,0.0003407869,0.001382372,0.0004267644,0.001279189,0.0008162526,0.0003564091,0.0008975437],"category_scores_gemma":[0.02877895,0.0001276811,0.0004305253,0.001208785,0.0008654922,0.0007275534,0.0006728098,0.0005730063,0.0003809444],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002653131,"about_ca_system_score_gemma":0.002305554,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3567318,"about_ca_topic_score_gemma":0.2706652,"domain_scores_codex":[0.9975474,0.0007761023,0.0002466009,0.0002519998,0.0009581601,0.0002196921],"domain_scores_gemma":[0.9890562,0.002164917,0.003184233,0.001566875,0.003569955,0.0004578719],"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":[0.0001191334,0.00003144973,0.9541917,0.00004127331,0.0001118252,0.00003457105,0.0007253131,0.005712567,0.000336244,0.004504777,0.002097217,0.03209401],"study_design_scores_gemma":[0.000007272273,0.0001557746,0.9749637,0.000089435,0.00005306814,0.00009513935,0.001302629,0.01418558,0.001611544,0.001842808,0.005643851,0.00004914417],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9489985,0.001331655,0.02541173,0.001767421,0.0001444466,0.00009378616,0.003262958,0.0002116114,0.01877783],"genre_scores_gemma":[0.9960539,0.0001121195,0.002612758,0.00006284704,0.00001145733,0.000008569843,0.0005107823,0.000007058348,0.0006205473],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3567318,"threshold_uncertainty_score":0.7093107,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09428533221366701,"score_gpt":0.3417461778732872,"score_spread":0.2474608456596202,"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."}}