{"id":"W4399481146","doi":"10.4000/11slt","title":"Quand l’humanitaire reproduit de profondes inégalités de carrière","year":2024,"lang":"fr","type":"article","venue":"Formation emploi","topic":"Multiculturalism, Politics, Migration, Gender","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"International Development Research Centre; Université de Moncton","funders":"","keywords":"Political 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":[0.001148771,0.0002262305,0.0001846148,0.0001160384,0.0006072689,0.0005367669,0.0002402731,0.000287268,0.0006321931],"category_scores_gemma":[0.0003307604,0.0002220571,0.0001467952,0.0003354496,0.0004715161,0.002022612,0.00004453906,0.0002931424,0.0007317396],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002777556,"about_ca_system_score_gemma":0.001124941,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008363797,"about_ca_topic_score_gemma":0.005379983,"domain_scores_codex":[0.9975693,0.0003973439,0.0005155849,0.0003288407,0.0004730316,0.0007158512],"domain_scores_gemma":[0.9989961,0.0001035231,0.0001226329,0.0002780501,0.0002672275,0.000232422],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000007134067,0.00005520981,0.006949278,0.0008681164,0.00008049121,0.00001447906,0.5544569,0.0001661039,0.0002714224,0.3348211,0.09613716,0.006172572],"study_design_scores_gemma":[0.000189297,0.00005571821,0.01570935,0.0003333935,0.0001110932,0.00005313598,0.05336845,0.00552677,0.001361893,0.00707017,0.9158101,0.0004105923],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9271379,0.007031346,0.001739941,0.04167496,0.002597232,0.0007742011,0.0001537444,0.0005192435,0.01837149],"genre_scores_gemma":[0.9020026,0.0002698842,0.0005833312,0.002103552,0.001327059,0.00005808939,0.0001001606,0.00003364879,0.09352165],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.819673,"threshold_uncertainty_score":0.9982396,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2195748304512406,"score_gpt":0.4232685483463284,"score_spread":0.2036937178950879,"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."}}