{"id":"W2101516143","doi":"10.25336/p6r317","title":"The long goodbye: Age, demographics, and flexibility in retirement","year":2012,"lang":"en","type":"article","venue":"Canadian Studies in Population","topic":"Retirement, Disability, and Employment","field":"Social Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan; University of Toronto","funders":"Government of Canada","keywords":"Life expectancy; Baby boom; Aging in the American workforce; Demographics; Retirement age; Flexibility (engineering); Workforce; Labour economics; Preference; Demographic economics; Economics; Economic growth; Sociology; Population; Demography; Finance; Management","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.002189301,0.0000788086,0.000116311,0.00008592303,0.0006246413,0.00003283911,0.00008734146,0.00005493343,0.000007244865],"category_scores_gemma":[0.0005903821,0.00006656381,0.00002259101,0.0003118161,0.0004814078,0.0001479898,0.00003030921,0.00008596487,0.000001614167],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001119357,"about_ca_system_score_gemma":0.0000501723,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.4120541,"about_ca_topic_score_gemma":0.9899772,"domain_scores_codex":[0.9986774,0.0002514973,0.0002459532,0.0001608724,0.0001988516,0.0004653702],"domain_scores_gemma":[0.9994888,0.0001121115,0.00004305729,0.0001530292,0.00003303969,0.0001699519],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000002632112,0.00001337994,0.969586,0.00001049442,0.000007194194,8.339268e-7,0.00991722,0.000003752762,1.329544e-7,0.01304609,0.0001913149,0.007221016],"study_design_scores_gemma":[0.00008815477,0.000007196832,0.9788141,0.00002326505,0.000004068169,5.655862e-8,0.01095247,0.000006214419,3.950827e-7,0.005360473,0.004667062,0.00007651111],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9887465,0.004417766,6.664364e-7,0.001723416,0.0006225191,0.0004462075,0.000001938521,0.00001008544,0.004030966],"genre_scores_gemma":[0.9979291,0.001701108,0.00001636217,0.0001010729,0.0001104139,0.00004063157,0.000004353005,0.000004261177,0.00009269976],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5779231,"threshold_uncertainty_score":0.5918611,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3655575945513204,"score_gpt":0.4765278502055104,"score_spread":0.1109702556541901,"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."}}