{"id":"W2746410442","doi":"10.25222/larr.62","title":"Inequality and Inclusion in Latin America","year":2017,"lang":"en","type":"article","venue":"Latin American Research Review","topic":"Income, Poverty, and Inequality","field":"Social Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Cambridge; International Development Research Centre; Carter Center; Woodrow Wilson International Center for Scholars; Ford Foundation","keywords":"Latin Americans; Inequality; Inclusion (mineral); Political science; Sociology; Gender studies; Mathematics; Law","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":["metaresearch","sts"],"consensus_categories":["sts"],"category_scores_codex":[0.01171566,0.0001362892,0.0005753022,0.000102786,0.004289159,0.0001685537,0.001012345,0.00005205954,0.0003639437],"category_scores_gemma":[0.01106258,0.0001154864,0.00006937966,0.0006774185,0.002732418,0.0002825041,0.004666682,0.0005535707,0.000062493],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00019728,"about_ca_system_score_gemma":0.0002854789,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09508873,"about_ca_topic_score_gemma":0.009187887,"domain_scores_codex":[0.9938977,0.003146719,0.0004688797,0.0004095068,0.001385019,0.0006921655],"domain_scores_gemma":[0.997546,0.0007867719,0.0003563889,0.0008096463,0.0002365657,0.0002645962],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001838077,0.00009715406,0.1161658,0.0006787415,0.000006885863,0.00001413727,0.007885264,1.064469e-7,0.00003650007,0.009482875,0.003321855,0.8622922],"study_design_scores_gemma":[0.0002720751,0.0001688347,0.2829371,0.001960293,0.000007602166,2.006155e-7,0.001802166,0.00006712296,0.000007723596,0.008340392,0.7041269,0.0003095713],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3788423,0.03101341,0.00006838078,0.08308284,0.0002587248,0.002744413,0.00004320774,0.0001191596,0.5038276],"genre_scores_gemma":[0.8463728,0.1497095,0.0006859278,0.002101359,0.0001773357,0.00006141741,0.000005071609,0.00001352686,0.000873034],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8619827,"threshold_uncertainty_score":0.9999816,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2206187715058664,"score_gpt":0.5035051812789313,"score_spread":0.2828864097730649,"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."}}