{"id":"W4416007086","doi":"10.5465/amproc.2025.18593symposium","title":"Opening the “Black Box” of Algorithmic Management and Control: New Theory and Empirical Directions","year":2025,"lang":"en","type":"article","venue":"Academy of Management Proceedings","topic":"Ethics and Social Impacts of AI","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Casual; Unintended consequences; Empirical research; Creativity; Field (mathematics); Focus (optics); Empirical evidence; Stock (firearms)","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":[],"consensus_categories":[],"category_scores_codex":[0.002616433,0.0001030496,0.0001975724,0.0001322689,0.0004614665,0.0001178877,0.0003043628,0.0001169489,0.00001464639],"category_scores_gemma":[0.0001816503,0.00008347314,0.00004531843,0.0003869261,0.0007379532,0.0003202067,0.0002455856,0.0002295269,8.072915e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002708034,"about_ca_system_score_gemma":0.0000203023,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000149031,"about_ca_topic_score_gemma":0.000005645413,"domain_scores_codex":[0.9989594,0.00005732658,0.0002510554,0.0001892133,0.0003172353,0.0002258075],"domain_scores_gemma":[0.9994323,0.000252252,0.0001406991,0.00004050272,0.00005880503,0.00007546854],"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":[0.00003508108,0.00002157028,0.002144635,0.0001572151,0.0002374518,2.706846e-7,0.01036543,5.635789e-7,0.00002104012,0.9463817,0.01040792,0.03022707],"study_design_scores_gemma":[0.001355282,0.00005720441,0.07537784,0.0003416928,0.0005429554,4.208739e-7,0.0646381,0.00004684529,0.00018696,0.5575365,0.2996965,0.0002196613],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1823192,0.002376154,0.001277953,0.1491891,0.0001486105,0.001976846,0.000004078588,0.00009353069,0.6626145],"genre_scores_gemma":[0.974989,0.004898065,0.0007046078,0.002249034,0.00007045829,0.00001519344,1.646511e-7,0.000007447643,0.01706602],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7926698,"threshold_uncertainty_score":0.3549274,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03213192249877289,"score_gpt":0.3759094289108271,"score_spread":0.3437775064120542,"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."}}