{"id":"W2953230249","doi":"10.1287/orsc.2018.1259","title":"One Step Forward, Two Steps Back: How Negative External Evaluations Can Shorten Organizational Time Horizons","year":2019,"lang":"en","type":"article","venue":"Organization Science","topic":"Financial Markets and Investment Strategies","field":"Economics, Econometrics and Finance","cited_by":76,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Operationalization; New horizons; Context (archaeology); Organizational theory; Cognition; Organizational learning; Organizational behavior; Earnings; Time horizon; Business; Economics; Psychology; Finance; Management; Epistemology","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":[0.004603596,0.0003259413,0.0003019555,0.0009136791,0.0009112291,0.004654564,0.0004654027,0.0008923427,0.00822299],"category_scores_gemma":[0.02887023,0.0002229129,0.0003882041,0.0007580124,0.002031802,0.004759112,0.001894395,0.002171517,0.0005932019],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001223768,"about_ca_system_score_gemma":0.001314179,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00287968,"about_ca_topic_score_gemma":0.003948648,"domain_scores_codex":[0.9982421,0.0006942899,0.00009617391,0.0002927004,0.0003721486,0.0003025596],"domain_scores_gemma":[0.9656557,0.0137898,0.01245487,0.002217034,0.002202071,0.00368054],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001684665,0.001069741,0.609083,0.0005067307,0.000383175,0.000567038,0.02621642,0.003266541,0.009282969,0.1213638,0.006627602,0.2199484],"study_design_scores_gemma":[0.00009943043,0.000764238,0.8904732,0.0002838548,0.0001602807,0.0001919881,0.01190848,0.002233232,0.002758599,0.07961122,0.01137961,0.0001358954],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9305297,0.001165918,0.007273039,0.01307981,0.0001811068,0.0000442718,0.0002574793,0.00005989917,0.04740867],"genre_scores_gemma":[0.9974252,0.0001444391,0.000891788,0.0003495334,0.00004520562,0.00001112831,0.00004367895,0.00001566077,0.001073356],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00822299,"threshold_uncertainty_score":0.02750868,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02214086537949746,"score_gpt":0.2316739057308516,"score_spread":0.2095330403513541,"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."}}