{"id":"W1546741540","doi":"","title":"Pension Funds and Incentive Compensation: A Story Based on the Ontario Teachers' Experience","year":2009,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Financial Literacy, Pension, Retirement Analysis","field":"Business, Management and Accounting","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Incentive; Compensation (psychology); Pension; Benchmark (surveying); Investment (military); Plan (archaeology); Actuarial science; Pension fund; Pension plan; Pension system; Business; Finance; Accounting; Economics; Microeconomics; Political science; Psychology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001317492,0.0001875454,0.0001790484,0.0001983025,0.0007806529,0.0002664216,0.0002348966,0.00005050559,0.0002681956],"category_scores_gemma":[0.0001039952,0.0001340522,0.0001008985,0.0003138777,0.00006390024,0.0006663412,0.00003864108,0.001161835,0.000047721],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007198317,"about_ca_system_score_gemma":0.0003408974,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001851988,"about_ca_topic_score_gemma":0.0195064,"domain_scores_codex":[0.998175,0.00004877089,0.0002279376,0.0002476939,0.000433821,0.0008667937],"domain_scores_gemma":[0.99931,0.0000540586,0.0002647768,0.0001997934,0.0001553602,0.00001602299],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004336959,0.00031318,0.7214398,0.000008371908,0.0000445094,0.00002115575,0.003459472,0.0001853837,0.0006595535,0.2561557,0.001703562,0.01557559],"study_design_scores_gemma":[0.001645347,0.0003104892,0.8839829,0.0001580704,0.0001914176,0.00001840433,0.004153346,0.009009699,0.00003879266,0.05498509,0.04489426,0.0006122024],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.994344,0.0002038699,0.0002740769,0.002654154,0.0001170956,0.0001499152,1.388711e-7,0.00002794446,0.002228835],"genre_scores_gemma":[0.9952618,0.00003782743,0.00003727531,0.003194561,0.0004144378,0.000003408629,0.000006936742,0.00001096098,0.001032807],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2011706,"threshold_uncertainty_score":0.9983851,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01111963332312802,"score_gpt":0.2152220433083008,"score_spread":0.2041024099851728,"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."}}