{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002994879,0.0001147577,0.0001874407,0.0009784517,0.001615527,0.0013113,0.000463819,0.0006194501,0.00602236],"category_scores_gemma":[0.008941625,0.00009792743,0.0002629812,0.001109393,0.001732099,0.002143213,0.001210602,0.0008602767,0.0003339559],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00275385,"about_ca_system_score_gemma":0.002959004,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3097245,"about_ca_topic_score_gemma":0.503004,"domain_scores_codex":[0.9993042,0.0002361594,0.00002823951,0.00005939082,0.0001852263,0.0001867368],"domain_scores_gemma":[0.9967077,0.0006778848,0.0007403126,0.0001978331,0.0004960751,0.001180125],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001495692,0.0001021787,0.8959045,0.0000415893,0.00004904022,0.000107482,0.009209009,0.0004246015,0.0001680984,0.02428182,0.008344255,0.0612176],"study_design_scores_gemma":[0.000003467489,0.00003908232,0.9732077,0.00008875118,0.00001475702,0.00007476286,0.00667725,0.0002235562,0.00003934027,0.006046567,0.0135616,0.00002324263],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9152606,0.01008128,0.001120224,0.04892198,0.0001417042,0.00002816442,0.001000131,0.00001381191,0.02343218],"genre_scores_gemma":[0.9961196,0.001063831,0.0001562481,0.0007038798,0.00005096728,0.000004583421,0.0001118848,0.000003237745,0.001785889],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6902754,"threshold_uncertainty_score":0.6158435,"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."}}