{"id":"W4280564614","doi":"10.3390/jrfm15050217","title":"Nudges and Networks: How to Use Behavioural Economics to Improve the Life Cycle Savings-Consumption Balance","year":2022,"lang":"en","type":"article","venue":"Journal of risk and financial management","topic":"Financial Literacy, Pension, Retirement Analysis","field":"Business, Management and Accounting","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Nudge theory; Consumption (sociology); Economics; Balance (ability); Legislature; Unintended consequences; Public economics; Pension; Actuarial science; Labour economics; Business; Finance; Political science; Medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008725765,0.0001918793,0.0003068461,0.0003540138,0.0006606532,0.0005848325,0.0002784586,0.00003117638,0.00003795044],"category_scores_gemma":[0.0001814305,0.0001590847,0.0001128271,0.0003722254,0.0000357236,0.0008099467,0.0006946141,0.0002478392,0.000007245662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000062213,"about_ca_system_score_gemma":0.00001189944,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002927707,"about_ca_topic_score_gemma":0.0001986667,"domain_scores_codex":[0.9987497,0.0000301854,0.0004232965,0.0002699333,0.0002495838,0.0002773342],"domain_scores_gemma":[0.9990382,0.00005420504,0.0005407872,0.0002032989,0.0001121994,0.00005127376],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003116089,0.00007263225,0.9337274,0.00003759599,0.00002211083,0.00002765076,0.0002393321,0.004453273,0.00001076085,0.00462849,0.007058465,0.04941064],"study_design_scores_gemma":[0.0005144649,0.00007204952,0.8735689,0.00002723009,0.0003023862,0.000003571135,0.0002375187,0.003476808,0.000001191795,0.0004934703,0.1210927,0.0002096948],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9958522,0.0003192716,0.001502304,0.001150485,0.0007424653,0.0003772738,0.00001207241,0.00001378623,0.00003009281],"genre_scores_gemma":[0.9942977,0.0006787389,0.0006285324,0.003502155,0.0006881237,0.00002721189,0.000004859577,0.00001987234,0.0001528422],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1140343,"threshold_uncertainty_score":0.6487284,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01058869253109144,"score_gpt":0.1954487574901186,"score_spread":0.1848600649590272,"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."}}