{"id":"W3217504687","doi":"10.3167/latiss.2021.140303","title":"Understanding networks of actors involved in refugee access to higher education in Canada, England and France","year":2021,"lang":"en","type":"article","venue":"Learning and Teaching","topic":"Education and experiences of immigrants and refugees","field":"Social Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Universiteit van Amsterdam","keywords":"Refugee; Government (linguistics); Civil society; Higher education; Context (archaeology); Political science; Economic growth; Access to Higher Education; Public administration; Sociology; Public relations; Politics; Law; Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003429342,0.00004767415,0.00009939603,0.0000603642,0.0002397365,0.00007073197,0.00005239779,0.00003574148,0.00002556944],"category_scores_gemma":[0.0001248616,0.00004431642,0.000006810479,0.000125657,0.00003525545,0.000137712,0.00002396462,0.0002226679,5.696589e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001124583,"about_ca_system_score_gemma":0.0005147096,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.675336,"about_ca_topic_score_gemma":0.9295791,"domain_scores_codex":[0.9993455,0.0001753971,0.0001163899,0.0001303696,0.00009521392,0.0001371426],"domain_scores_gemma":[0.9997313,0.0001145113,0.00004285077,0.00003197248,0.00001259969,0.00006677292],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000003081597,0.00001415476,0.9558185,0.00000901064,0.000001646805,9.474008e-7,0.02152322,0.0002903294,0.00002307127,0.00472147,0.00002884383,0.01756568],"study_design_scores_gemma":[0.0002218354,0.00001080335,0.7621477,0.0002619416,0.000002270908,3.182722e-7,0.08914748,0.0001667968,0.00001013276,0.0002195001,0.1476842,0.0001270731],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9944711,0.0007186869,0.00004346282,0.002046351,0.0003085647,0.00004034906,1.364588e-7,0.000004804064,0.002366508],"genre_scores_gemma":[0.9983586,0.0001926601,0.00006832819,0.0002023473,0.00007388849,0.000002657332,0.000001571063,0.000003253851,0.001096681],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2542431,"threshold_uncertainty_score":0.326826,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03785185006816977,"score_gpt":0.3363314622885025,"score_spread":0.2984796122203327,"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."}}