{"id":"W2953999747","doi":"10.5539/ijef.v11n7p110","title":"Exporting Transparency Through Mergers","year":2019,"lang":"en","type":"article","venue":"International Journal of Economics and Finance","topic":"Corruption and Economic Development","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal; Université de Sherbrooke","funders":"","keywords":"Openness to experience; Proxy (statistics); Transparency (behavior); Competition (biology); Language change; International economics; Economics; Monetary economics; Capital (architecture); Mergers and acquisitions; Business; Market economy; Finance; Political science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002836955,0.0003763126,0.0002982029,0.001943825,0.001454347,0.006031669,0.0004421685,0.001010935,0.02031094],"category_scores_gemma":[0.01600983,0.0003264871,0.0006921685,0.001728657,0.00286148,0.004071104,0.004503005,0.001613137,0.001434483],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001924715,"about_ca_system_score_gemma":0.002419834,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003298488,"about_ca_topic_score_gemma":0.003409067,"domain_scores_codex":[0.9968718,0.001149685,0.0001982659,0.0003619167,0.0006835738,0.0007348378],"domain_scores_gemma":[0.9813803,0.005537606,0.008110733,0.002448825,0.001262517,0.001259995],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.000413804,0.0004173389,0.1938296,0.0006426678,0.0002599509,0.002146594,0.008878133,0.005155876,0.007724712,0.5876853,0.01602192,0.1768241],"study_design_scores_gemma":[0.0003413862,0.001028184,0.3220793,0.001383257,0.0003173149,0.003161459,0.009207654,0.009245545,0.01328805,0.2697303,0.3700419,0.0001757432],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5470052,0.001459455,0.01270939,0.005722208,0.0001084573,0.0002758891,0.0005898006,0.0003566666,0.4317729],"genre_scores_gemma":[0.9815227,0.0005416705,0.001686787,0.0004904099,0.0001125753,0.00004613343,0.00012755,0.0000248795,0.0154473],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02031094,"threshold_uncertainty_score":0.06794685,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0287038089057416,"score_gpt":0.285894374327188,"score_spread":0.2571905654214464,"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."}}