{"id":"W4211156401","doi":"10.1016/j.jwb.2022.101312","title":"Managing socio-political risk at the subnational level: Lessons from MNE subsidiaries in Indonesia","year":2022,"lang":"en","type":"article","venue":"Journal of World Business","topic":"International Business and FDI","field":"Business, Management and Accounting","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Multinational corporation; Political risk; Extant taxon; Subsidiary; Emerging markets; Politics; Business; Government (linguistics); Economic geography; Variety (cybernetics); Political science; Economics; Finance","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009922622,0.0001949876,0.000311099,0.0007731459,0.0007008397,0.0003044007,0.0006096688,0.00003419319,0.001663977],"category_scores_gemma":[0.0002062361,0.0001493539,0.0001448474,0.001455296,0.0001366255,0.0009959041,0.0005744575,0.0005589746,0.00004558155],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004012035,"about_ca_system_score_gemma":0.0001336611,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002477079,"about_ca_topic_score_gemma":0.001974994,"domain_scores_codex":[0.9977985,0.00005603457,0.0006376376,0.000201177,0.000950108,0.0003565451],"domain_scores_gemma":[0.9979996,0.0003160031,0.0007967453,0.0001678691,0.0007019691,0.00001781481],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005303554,0.0003327169,0.7231324,0.00004776391,0.0001394478,0.0002979836,0.0001245362,0.009370555,0.0001773529,0.2482555,0.01419801,0.003393402],"study_design_scores_gemma":[0.001096026,0.000003318292,0.9034092,0.0000501459,0.00008519059,0.00003423907,0.0005504229,0.001563255,0.00001771095,0.04243954,0.05053807,0.000212914],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.904391,0.0003650165,0.0006665462,0.08975223,0.001770367,0.0001216219,0.00005721079,0.00001884076,0.002857192],"genre_scores_gemma":[0.9939543,0.00002001142,0.00006800438,0.00278467,0.002363531,0.00001485893,0.00006439901,0.00003224298,0.0006979968],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2058159,"threshold_uncertainty_score":0.9992486,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03170630693006793,"score_gpt":0.2581235310810017,"score_spread":0.2264172241509338,"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."}}