{"id":"W2283476676","doi":"10.1057/9781137467720_40","title":"Improving IB Learning through Multidisciplinary Simulations: Lessons from a Mock-Up of EU-US Trade Negotiations","year":2015,"lang":"en","type":"book-chapter","venue":"Palgrave Macmillan UK eBooks","topic":"Innovative Teaching Methodologies in Social Sciences","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Multidisciplinary approach; Negotiation; Accreditation; Curriculum; International business; Quarter (Canadian coin); Engineering ethics; Political science; Engineering; Public relations; Pedagogy; Sociology; Law; History","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.002682449,0.0007826702,0.0003524509,0.0004948371,0.003325942,0.003985634,0.002228332,0.002761303,0.007979312],"category_scores_gemma":[0.005724504,0.0003124007,0.0005365689,0.0006753004,0.002830763,0.002786524,0.00524255,0.002807992,0.001822176],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001431664,"about_ca_system_score_gemma":0.001217389,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001080127,"about_ca_topic_score_gemma":0.003357097,"domain_scores_codex":[0.9985019,0.001066098,0.00004050955,0.00007076244,0.0001747495,0.00014608],"domain_scores_gemma":[0.9965894,0.002432434,0.00007558246,0.0002347406,0.0001822629,0.00048558],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0006520915,0.00653906,0.007477007,0.001308873,0.00008887429,0.009100724,0.2385112,0.05885317,0.007594116,0.1971869,0.1345596,0.3381283],"study_design_scores_gemma":[0.0002940188,0.001330425,0.007200518,0.001222901,0.0000364325,0.002558492,0.1436741,0.0325272,0.01057553,0.1185028,0.6818885,0.0001891988],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6735057,0.002327728,0.03669702,0.009805161,0.0006940613,0.0004702636,0.0002952505,0.0004617818,0.2757429],"genre_scores_gemma":[0.8936201,0.001730033,0.04294233,0.001465783,0.0000848764,0.0003490562,0.0003910414,0.0002643901,0.05915238],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007979312,"threshold_uncertainty_score":0.0266934,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1666839971775805,"score_gpt":0.4024249254115185,"score_spread":0.2357409282339381,"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."}}