{"id":"W2097176971","doi":"","title":"Multidimensional Poverty and Material Deprivation","year":2009,"lang":"en","type":"article","venue":"Papyrus : Institutional Repository (Université de Montréal)","topic":"Income, Poverty, and Inequality","field":"Social Sciences","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada; Ministero dell’Istruzione, dell’Università e della Ricerca","keywords":"Poverty; Inequality; Contrast (vision); Class (philosophy); Econometrics; Relative deprivation; European union; Feature (linguistics); Economics; Mathematics; Psychology; Demographic economics; Social psychology; Computer science; Artificial intelligence; Economic growth","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001269163,0.000335204,0.0002915207,0.002743079,0.001109015,0.001739098,0.0004391374,0.0003964519,0.003515393],"category_scores_gemma":[0.004781885,0.00009613174,0.0003976499,0.003315552,0.003590957,0.00190587,0.003678366,0.0008263253,0.0001712465],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001719201,"about_ca_system_score_gemma":0.0008292861,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003785368,"about_ca_topic_score_gemma":0.005335082,"domain_scores_codex":[0.998695,0.0005684493,0.00006000051,0.0001286413,0.0003641192,0.0001838744],"domain_scores_gemma":[0.9971613,0.0008478217,0.001162691,0.0002958175,0.000328352,0.0002041165],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00002462949,0.00007149672,0.03366042,0.0001352745,0.00004814646,0.0001299305,0.002555603,0.002445116,0.0004344416,0.8959971,0.00213088,0.06236695],"study_design_scores_gemma":[0.000009674602,0.0001658196,0.1464435,0.000523688,0.00005139179,0.0006891622,0.005252063,0.01234581,0.00119579,0.7797273,0.0535152,0.00008059313],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5495119,0.005821552,0.147057,0.01272834,0.0002823891,0.00018492,0.001223783,0.0000720335,0.2831181],"genre_scores_gemma":[0.9829759,0.001055132,0.01310756,0.0002275876,0.00006803473,0.00009838516,0.00009589642,0.000007218577,0.002364235],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003785368,"threshold_uncertainty_score":0.01247376,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009334907572234274,"score_gpt":0.2055946314522434,"score_spread":0.1962597238800091,"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."}}