{"id":"W7081966895","doi":"10.1016/j.frl.2025.108468","title":"Hidden costs of government-guided funds: Evidence from executive-employee pay gaps","year":2025,"lang":"en","type":"article","venue":"Finance research letters","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University; Saint Mary's University","funders":"Social Science Planning Project of Shandong Province; Natural Science Foundation of Shandong Province; Western University","keywords":"Unintended consequences; Executive compensation; Agency cost; Cash; Government (linguistics); Agency (philosophy); Compensation (psychology); Pay for performance","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.005199118,0.0002511451,0.000375748,0.00148724,0.0007596908,0.00153168,0.0009229378,0.0009355012,0.004931211],"category_scores_gemma":[0.02939698,0.0001656807,0.0005784649,0.00147572,0.00163267,0.001852692,0.002427229,0.001218572,0.0002825217],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002062086,"about_ca_system_score_gemma":0.002978997,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01171045,"about_ca_topic_score_gemma":0.01225584,"domain_scores_codex":[0.9962696,0.001308937,0.00024235,0.000383603,0.0009622657,0.0008332232],"domain_scores_gemma":[0.940862,0.02519289,0.02597891,0.00263461,0.002479603,0.002851957],"domain_codex":null,"domain_gemma":"incentives","domain_candidate":"incentives","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007415013,0.0004296735,0.9548716,0.0002039815,0.000227906,0.0003134228,0.001723758,0.0005901802,0.0001968545,0.003891657,0.0009927591,0.03581683],"study_design_scores_gemma":[0.00004152479,0.0002393062,0.992785,0.0001129035,0.0001637523,0.00009374556,0.002372108,0.0007263483,0.0003509592,0.001612861,0.001487798,0.00001375844],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9942659,0.0009002939,0.0001745423,0.001096287,0.00001359544,0.00001833595,0.0002088879,0.000004740206,0.003317381],"genre_scores_gemma":[0.9993783,0.0001991299,0.00004362888,0.00008896472,0.00001463116,0.000007305699,0.00006337814,0.000001306504,0.0002032282],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9948009,"threshold_uncertainty_score":0.02749592,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05968017054901332,"score_gpt":0.3295720976049105,"score_spread":0.2698919270558972,"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."}}