{"id":"W3034633082","doi":"10.6000/1929-7092.2020.09.24","title":"Philippine Household Income Mobility Measurement and its Decomposition using a Pseudo-Longitudinal Panel Data","year":2020,"lang":"en","type":"article","venue":"Journal of Reviews on Global Economics","topic":"Income, Poverty, and Inequality","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Economics; Income distribution; Total personal income; Poverty; Net national income; Index (typography); Economic inequality; Economic mobility; Demographic economics; Welfare; Distribution (mathematics); Income in kind; Panel data; Comprehensive income; Household income; Labour economics; Social mobility; Inequality; Gross income; Econometrics; Economic growth; Geography; Public economics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00191526,0.0003632942,0.0002494429,0.001135844,0.000504198,0.0005339396,0.0004628995,0.0002181597,0.004377878],"category_scores_gemma":[0.002849247,0.0001510627,0.0007045359,0.002508931,0.0002174478,0.0004773597,0.0008854956,0.0007070869,0.0006382704],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008352363,"about_ca_system_score_gemma":0.0008237872,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04846885,"about_ca_topic_score_gemma":0.02970514,"domain_scores_codex":[0.9992212,0.0004268271,0.00005213787,0.0001152914,0.0001006561,0.00008387093],"domain_scores_gemma":[0.9986677,0.0002757268,0.0004274379,0.0002065933,0.0003466928,0.00007596635],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001343985,0.0001222051,0.9409594,0.00009391402,0.0002985782,0.000191984,0.000834153,0.005802903,0.0003032252,0.003490143,0.008794709,0.03897452],"study_design_scores_gemma":[0.00001596229,0.000179503,0.9495941,0.00007559612,0.0001024555,0.0001198695,0.00174266,0.03446762,0.0006294706,0.002237765,0.01080191,0.00003307384],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9587662,0.0003461141,0.01742555,0.0006887609,0.00005182598,0.0002554253,0.01840279,0.0001458477,0.003917553],"genre_scores_gemma":[0.9708972,0.0002434985,0.008961484,0.00006652335,0.00002798523,0.0006570414,0.01675163,0.00001556016,0.002379043],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04846885,"threshold_uncertainty_score":0.0963735,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3740523298768031,"score_gpt":0.3899971522910328,"score_spread":0.01594482241422968,"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."}}