{"id":"W4297998822","doi":"10.32920/ryerson.14638719.v2","title":"Empirical Issues in Lifetime Poverty Measurement","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Income, Poverty, and Inequality","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"United Nations University World Institute for Development Economics Research; Department for International Development; Styrelsen för Internationellt Utvecklingssamarbete","keywords":"Poverty; Pairwise comparison; Economics; Weighting; Econometrics; Consumption (sociology); Perspective (graphical); Basic needs; Demographic economics; Statistics; Sociology; Computer science; Economic growth; Mathematics; Social science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.005667105,0.0002382909,0.0004700909,0.0001333326,0.0003673633,0.0001336346,0.0008106759,0.0003417744,0.01582721],"category_scores_gemma":[0.0008426416,0.0002176865,0.0002131193,0.0002568147,0.0001253272,0.0001015038,0.001043443,0.0009018076,0.0001340333],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001634496,"about_ca_system_score_gemma":0.001096594,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.06505527,"about_ca_topic_score_gemma":0.02445682,"domain_scores_codex":[0.9948794,0.00134301,0.0005342872,0.0005908937,0.002136502,0.0005158779],"domain_scores_gemma":[0.99893,0.00009726607,0.0001439012,0.0005004999,0.0001703578,0.0001579869],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008353932,0.001082857,0.2322123,0.0001683478,0.0001033111,0.00003460275,0.05382774,0.0001684161,0.00001298232,0.03041445,0.6794873,0.002404193],"study_design_scores_gemma":[0.0002018718,0.00003604941,0.03207593,0.00003606234,0.00001352172,1.096307e-7,0.004204857,0.00006213191,0.00001669517,0.0150774,0.9478557,0.000419753],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01948488,0.001203446,0.000119444,0.03721157,0.003282063,0.0008843991,0.00004299734,0.0002827259,0.9374885],"genre_scores_gemma":[0.9366554,0.001445274,0.0009333487,0.01426232,0.002029167,0.0002447956,0.00006277174,0.00005147273,0.04431545],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9171705,"threshold_uncertainty_score":0.9933443,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1290637715549173,"score_gpt":0.3992600411610134,"score_spread":0.2701962696060961,"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."}}