{"id":"W4400177602","doi":"10.1080/23311886.2024.2361527","title":"Poverty alleviation programs in Nigeria: a study on World Mission Agency (WMA) using principal component analysis","year":2024,"lang":"en","type":"article","venue":"Cogent Social Sciences","topic":"Religion, Society, and Development","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Redeemer University","funders":"","keywords":"Poverty; Grassroots; Agency (philosophy); Government (linguistics); Economic growth; Developing country; Basic needs; Poverty reduction; Political science; Development economics; Economics; Sociology; Social science; Politics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001812417,0.0001702884,0.000206108,0.0006921771,0.002364072,0.00144516,0.0002211839,0.0003542514,0.001159531],"category_scores_gemma":[0.003047761,0.0002724542,0.0001344626,0.001344362,0.000658489,0.001291627,0.0008202583,0.0008050466,0.0001319545],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009877284,"about_ca_system_score_gemma":0.002418099,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009774401,"about_ca_topic_score_gemma":0.02473495,"domain_scores_codex":[0.9992693,0.0004000817,0.00003483548,0.00002642038,0.00009283466,0.0001765664],"domain_scores_gemma":[0.9986571,0.0004306515,0.0004008633,0.00003421992,0.0002011307,0.0002760327],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001351293,0.002032333,0.6680372,0.0003111208,0.00002613141,0.001571735,0.2560108,0.0001472297,0.00133357,0.004298592,0.002217827,0.0638783],"study_design_scores_gemma":[0.00001146907,0.0004786894,0.5915936,0.00031536,0.00001618948,0.0004982569,0.3961737,0.0002487349,0.0002122783,0.0003364403,0.01009732,0.00001788154],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985127,0.0001412052,0.00002551003,0.0002240534,0.000005086785,0.00002107101,0.000009906205,4.053279e-7,0.00106003],"genre_scores_gemma":[0.9983979,0.0007577337,0.000108066,0.00008464285,0.000003783963,0.0000338467,0.00001597054,9.714629e-7,0.0005971023],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009774401,"threshold_uncertainty_score":0.01943499,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1528578439387239,"score_gpt":0.4043710691085279,"score_spread":0.251513225169804,"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."}}