{"id":"W2748203928","doi":"10.1016/j.orgdyn.2015.05.010","title":"Racing to the bottom: The negative consequences of organizational speed","year":2015,"lang":"en","type":"article","venue":"Organizational Dynamics","topic":"Human Resource and Talent Management","field":"Business, Management and Accounting","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"U.S. Food and Drug Administration","keywords":"Top-down and bottom-up design; Business; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001762907,0.0002330552,0.0002379126,0.001057961,0.002134336,0.004109984,0.0006431275,0.001392608,0.009339159],"category_scores_gemma":[0.01438708,0.0002327268,0.0002099091,0.0008136886,0.002260463,0.002359201,0.001535284,0.001612694,0.001000573],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008806176,"about_ca_system_score_gemma":0.001247604,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003176472,"about_ca_topic_score_gemma":0.003544323,"domain_scores_codex":[0.99862,0.0005438567,0.00004480224,0.0001617868,0.0003324783,0.0002970306],"domain_scores_gemma":[0.9857687,0.005149381,0.003533947,0.001307854,0.001625244,0.002614858],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00213114,0.001280518,0.4423383,0.0003751331,0.0002738454,0.001863843,0.03875498,0.009086481,0.01850471,0.1018381,0.04612168,0.3374313],"study_design_scores_gemma":[0.0001053127,0.0005646157,0.7509528,0.0003739975,0.0001544081,0.001035726,0.06709457,0.00894946,0.003838861,0.1267708,0.03998186,0.0001775429],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9566894,0.0004677611,0.001272925,0.00576342,0.0001511548,0.00001019423,0.00005008046,0.00003141876,0.03556374],"genre_scores_gemma":[0.9979112,0.0001529819,0.0002560054,0.0002560208,0.00004193122,0.000006004935,0.00001427887,0.00001593708,0.001345716],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009339159,"threshold_uncertainty_score":0.03124261,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01707709926557692,"score_gpt":0.2184509052620315,"score_spread":0.2013738059964546,"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."}}