{"id":"W2922061234","doi":"10.3390/soc9010019","title":"Policy Coherence and Social Protection in Ethiopia: Ensuring No One Is Left Behind","year":2019,"lang":"en","type":"article","venue":"Societies","topic":"Poverty, Education, and Child Welfare","field":"Social Sciences","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"United States Agency for International Development","keywords":"Coherence (philosophical gambling strategy); Government (linguistics); Set (abstract data type); Social protection; Resource (disambiguation); Public economics; Political science; Public relations; Economic growth; Economics; Computer 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":[],"consensus_categories":[],"category_scores_codex":[0.0003437522,0.00007150131,0.0001083408,0.00003844586,0.0005705128,0.00007886927,0.00009726864,0.0001571012,0.0002318026],"category_scores_gemma":[0.00004602888,0.00007866437,0.00003828191,0.00007393018,0.0001940321,0.000212247,0.00002117971,0.0001888142,0.00005668348],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000128203,"about_ca_system_score_gemma":0.0003464509,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00996709,"about_ca_topic_score_gemma":0.003348804,"domain_scores_codex":[0.9991727,0.00009291065,0.0001041481,0.0001639321,0.0002386512,0.0002276297],"domain_scores_gemma":[0.9997524,0.00002495524,0.00005514358,0.00006393276,0.00007145482,0.00003211112],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.00001143342,0.00007780154,0.08553992,0.0001243139,0.00002198765,1.267181e-7,0.8975825,6.356572e-7,0.0005754853,0.009149527,0.003148325,0.003767942],"study_design_scores_gemma":[0.0008233532,0.00008597626,0.7082649,0.0001205133,0.00001616713,8.748144e-7,0.1307206,0.00001508275,0.0008007261,0.03858676,0.1200388,0.0005262051],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9356821,0.0002067168,0.00000257121,0.01838401,0.0002814943,0.0002933914,0.000006185905,0.00004064777,0.04510293],"genre_scores_gemma":[0.9799846,0.0003526081,0.00004230896,0.0006135493,0.00061117,0.000009467175,0.000002069388,0.00000703307,0.01837713],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7668619,"threshold_uncertainty_score":0.9966256,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02161087541534527,"score_gpt":0.2837458423019479,"score_spread":0.2621349668866026,"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."}}