{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004179418,0.00009494645,0.0001776506,0.00002270813,0.0002238486,0.00002729853,0.0005165391,0.00005962348,0.0001785462],"category_scores_gemma":[0.00005604348,0.00003437551,0.00005665984,0.00003501946,0.001844924,0.00002871465,0.0003109631,0.00009576711,0.000007465482],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004560637,"about_ca_system_score_gemma":0.00002224031,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003601061,"about_ca_topic_score_gemma":0.0009338285,"domain_scores_codex":[0.9993259,0.00004956644,0.0002286753,0.0001541585,0.0001074405,0.0001342375],"domain_scores_gemma":[0.9985732,0.0005862267,0.00009037209,0.0006176995,0.0001143417,0.00001810657],"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":[0.00002659058,0.00006252459,0.0001638495,0.00001123681,0.00003657361,2.030004e-7,0.003451986,2.230836e-8,0.00004477036,0.948988,0.0157431,0.03147114],"study_design_scores_gemma":[0.00155637,0.0002208884,0.001194737,0.00007554475,0.00005495887,0.000002788622,0.005721278,0.00008408433,0.0004091313,0.02197615,0.9685706,0.0001335019],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7814292,0.0137005,0.0000888605,0.02803887,0.001480669,0.0005550421,0.0003029126,0.00009279713,0.1743112],"genre_scores_gemma":[0.9931065,0.003033649,0.00001407353,0.0001674397,0.000217741,0.000005327471,0.000002399808,0.000008086567,0.003444715],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9528275,"threshold_uncertainty_score":0.67977,"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."}}