{"id":"W2553925927","doi":"","title":"The Future of Critique: Mark Andrejevic on Power/Knowledge and the Big Data-Driven Decline of Symbolic Efficiency","year":2016,"lang":"en","type":"article","venue":"","topic":"Cybernetics and Technology in Society","field":"Arts and Humanities","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Power (physics); The Symbolic; Symbolic power; Big data; Sociology; Computer science; Political science; Psychology; Politics; Data mining; Law; Psychoanalysis","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.01416266,0.0009589293,0.001538607,0.003202188,0.006987594,0.01470347,0.002703897,0.01365646,0.005014629],"category_scores_gemma":[0.05004647,0.0004202722,0.0005241547,0.002575945,0.03701847,0.01950142,0.005596149,0.02001802,0.001504392],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007188599,"about_ca_system_score_gemma":0.00595314,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008209453,"about_ca_topic_score_gemma":0.008781727,"domain_scores_codex":[0.9899838,0.00619833,0.0003109549,0.001385704,0.001707763,0.0004133828],"domain_scores_gemma":[0.9420768,0.04850535,0.001248029,0.001997201,0.004929211,0.001243302],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001947047,0.00001674131,0.0001270646,0.0001314763,0.00001298293,0.00005028112,0.004842396,0.0001909061,0.00004524051,0.702038,0.2869954,0.005529961],"study_design_scores_gemma":[0.00002192271,0.000006735815,0.0001595427,0.0005093477,0.000008524235,0.00003554458,0.002364509,0.0005083587,0.0001283437,0.6567321,0.3394862,0.00003884586],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.0007158428,0.0290411,0.0009877339,0.9530247,0.006413895,0.0000044266,0.00002614444,0.00002812132,0.009758044],"genre_scores_gemma":[0.2234846,0.04011901,0.003545069,0.5714926,0.1120064,0.0001857162,0.00007794997,0.0006885312,0.04840012],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9930124,"threshold_uncertainty_score":0.07490021,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02120744850249112,"score_gpt":0.2568379794439947,"score_spread":0.2356305309415036,"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."}}