{"id":"W4417429723","doi":"10.1177/14761270251410675","title":"A time for monsters: Organizational knowing after large language models","year":2025,"lang":"en","type":"article","venue":"Strategic Organization","topic":"Management and Organizational Studies","field":"Business, Management and Accounting","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Foregrounding; Dialogical self; On Language; Dynamics (music); Organizational theory; Redistribution (election); Organizational learning","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":[],"category_scores_codex":[0.0001564733,0.0001930911,0.0001688952,0.0002754822,0.0003574868,0.0003453844,0.0001796813,0.00007431347,0.001532776],"category_scores_gemma":[0.0001150247,0.000192675,0.00003674765,0.001785623,0.00003023499,0.0009125034,0.0001782629,0.00005128759,0.0003189234],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004823787,"about_ca_system_score_gemma":0.00004433908,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001170529,"about_ca_topic_score_gemma":0.0000265159,"domain_scores_codex":[0.998983,0.000006778834,0.0002585484,0.0003109911,0.0001854679,0.000255217],"domain_scores_gemma":[0.9991654,0.00002946189,0.0001023477,0.0001500585,0.0005440393,0.000008679472],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00003614612,0.0001574603,0.01413906,0.0004007061,0.0001401355,0.000004115931,0.0002799352,0.0007716639,0.0007666527,0.9706101,0.01255482,0.0001391973],"study_design_scores_gemma":[0.008162986,0.00005083085,0.02336182,0.0005377957,0.001328657,0.000003065277,0.0116504,0.2472403,0.00135727,0.6646797,0.03887293,0.002754201],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3094063,0.001356242,0.3719824,0.006518194,0.001787049,0.00344912,0.0001121165,0.001988607,0.3034],"genre_scores_gemma":[0.9904589,0.000008486217,0.0005206391,0.002131523,0.0005961995,0.00002836135,0.0007527449,0.00005061241,0.005452534],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6810526,"threshold_uncertainty_score":0.9993799,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009106724771770387,"score_gpt":0.2124631250473839,"score_spread":0.2033564002756135,"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."}}