{"id":"W2959788963","doi":"10.1093/ohr/ohz021","title":"“You ask many questions, but you don’t give many answers”: Embracing the Mess in Conflict Studies Classrooms","year":2019,"lang":"en","type":"article","venue":"The Oral History Review","topic":"Oral History, Memory, Narrative Analysis","field":"Arts and Humanities","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Constructive; Plural; Meaning (existential); Sociology; Interview; Postmodernism; Politics; Epistemology; Aesthetics; Public relations; Media studies; Law; Political science; Process (computing)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03224217,0.0006485382,0.001099116,0.002250201,0.01738816,0.02038962,0.00289116,0.003687995,0.00521357],"category_scores_gemma":[0.05149825,0.0009829482,0.0005422211,0.001750097,0.02865302,0.01457147,0.01751831,0.01026615,0.00141607],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005116522,"about_ca_system_score_gemma":0.009483469,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002564908,"about_ca_topic_score_gemma":0.008359031,"domain_scores_codex":[0.9570717,0.03557636,0.0005960701,0.001187868,0.003388332,0.002179737],"domain_scores_gemma":[0.9482906,0.04133359,0.002811698,0.001741797,0.002387985,0.003434425],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00001586044,0.00005268432,0.0008132848,0.0002566462,0.000007052741,0.0006060101,0.9548246,0.00005641513,0.0003793519,0.01717485,0.006669794,0.01914341],"study_design_scores_gemma":[0.00001021486,0.00004803235,0.0005510257,0.0006502435,0.000008143947,0.0006514225,0.834404,0.00008640912,0.0004104276,0.007888951,0.1552718,0.00001932291],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6428176,0.02714649,0.0330227,0.1243861,0.003944998,0.0006045479,0.00009545944,0.0003547929,0.1676274],"genre_scores_gemma":[0.953955,0.00744564,0.006908054,0.007740255,0.0005004317,0.000396069,0.00003873798,0.0002130824,0.02280265],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03224217,"threshold_uncertainty_score":0.1705149,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08276155025746147,"score_gpt":0.2959175999969305,"score_spread":0.2131560497394691,"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."}}