{"id":"W4406856342","doi":"10.1111/obes.12662","title":"On My Own: Boosting Financial Literacy Among Disadvantaged Youth in Peru","year":2025,"lang":"en","type":"article","venue":"Oxford Bulletin of Economics and Statistics","topic":"Financial Literacy, Pension, Retirement Analysis","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Citi Foundation; International Development Research Centre; Ford Foundation","keywords":"Financial literacy; Disadvantaged; Boosting (machine learning); Economics; Literacy; Political science; Economic growth; Business; Finance; Computer science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.0003486683,0.0002153742,0.0004224959,0.0003580784,0.0001505136,0.0001984824,0.0001608625,0.00007425902,0.0002226059],"category_scores_gemma":[0.0006355805,0.000224068,0.00006639822,0.0001847727,0.00009655754,0.000145996,0.000164374,0.0001526245,0.00001296708],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003931722,"about_ca_system_score_gemma":0.00002927593,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008755093,"about_ca_topic_score_gemma":0.0005549952,"domain_scores_codex":[0.9986581,0.00001221303,0.0006520817,0.0003493304,0.0000659575,0.0002623676],"domain_scores_gemma":[0.9991046,0.0001995435,0.0003684274,0.000205696,0.0001074873,0.00001422013],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001770652,0.0001171343,0.5918064,0.0002733181,0.00001196827,0.00001073764,0.0001887864,0.0005798101,0.000002893346,0.3927573,0.002429761,0.01164485],"study_design_scores_gemma":[0.002862259,0.00009059619,0.6255161,0.0007971358,0.0003020618,3.403001e-7,0.000507715,0.07394096,0.00002016642,0.05994569,0.2350824,0.0009345941],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.989874,0.00005522993,0.0004329356,0.0001845608,0.0002326182,0.0001942025,0.0001120113,0.00001442192,0.008900031],"genre_scores_gemma":[0.994662,0.0002417947,0.002955464,0.001068893,0.0001469261,0.000008101368,0.0001643394,0.00002019065,0.0007322495],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3328116,"threshold_uncertainty_score":0.9137228,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007108717576064414,"score_gpt":0.2105100358480427,"score_spread":0.2034013182719783,"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."}}