{"id":"W2208631231","doi":"10.22004/ag.econ.158368","title":"Does Transparency Reduce Corruption?","year":2013,"lang":"en","type":"preprint","venue":"AgEcon Search (University of Minnesota, USA)","topic":"Corruption and Economic Development","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Transparency (behavior); Language change; Margin (machine learning); Agency (philosophy); Imperfect; Economics; Monetary economics; Business; Computer security; Computer science","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":["insufficient_payload"],"category_scores_codex":[0.0009655957,0.0002094415,0.0004318853,0.0002977481,0.000596726,0.00008324743,0.0009860251,0.0003744742,0.02769643],"category_scores_gemma":[0.00003848558,0.0002210588,0.0002335257,0.0001789577,0.000624651,0.000384065,0.0004325804,0.0004965685,0.001593815],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004091772,"about_ca_system_score_gemma":0.0009160619,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02637983,"about_ca_topic_score_gemma":0.02017106,"domain_scores_codex":[0.9979313,0.0002711997,0.0002679442,0.0005917659,0.0004508729,0.0004869205],"domain_scores_gemma":[0.9986215,0.0001176606,0.0002275633,0.000430934,0.0002730415,0.0003292979],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002127667,0.0006901941,0.04437444,0.0008059975,0.0005721396,0.0001266897,0.3260193,0.0003586779,0.0005747438,0.020609,0.02782552,0.5778306],"study_design_scores_gemma":[0.001335085,0.00008687455,0.1665718,0.0003860431,0.0001174939,0.000002036937,0.1180848,0.0005797709,0.00007751618,0.002068668,0.7094284,0.00126162],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9289855,0.00005060815,0.0004541334,0.007209782,0.001485911,0.0006442221,0.00009400073,0.00007298582,0.0610029],"genre_scores_gemma":[0.8917122,0.003336612,0.001862851,0.00006227296,0.0001690171,0.000003022582,0.0000760272,0.00001547693,0.1027624],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6816028,"threshold_uncertainty_score":0.9991835,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0643358693406405,"score_gpt":0.2971860387776674,"score_spread":0.2328501694370269,"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."}}