{"id":"W2317188857","doi":"10.1177/0896920513504603","title":"Interrogating the Algorithm: Debt, Derivatives and the Social Reconstruction of Stock Market Trading","year":2014,"lang":"en","type":"article","venue":"Critical Sociology","topic":"Housing, Finance, and Neoliberalism","field":"Economics, Econometrics and Finance","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Debt; Politics; Economics; Stock market; Algorithmic trading; Harm; Derivatives market; High-frequency trading; Institution; Stock (firearms); Alternative trading system; Market economy; Finance; Law; Political science","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":[0.002869981,0.0001784885,0.0001934528,0.00136388,0.004104361,0.006028429,0.000590259,0.001810096,0.0034535],"category_scores_gemma":[0.00821632,0.000144975,0.0001356752,0.0009837258,0.0409522,0.008770511,0.00347806,0.001754059,0.0002325183],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002871266,"about_ca_system_score_gemma":0.001384648,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003503239,"about_ca_topic_score_gemma":0.003915945,"domain_scores_codex":[0.9986162,0.0009849488,0.00002667558,0.0001346001,0.0001341953,0.000103343],"domain_scores_gemma":[0.9963048,0.002394104,0.0005289502,0.000359716,0.0002323959,0.0001799511],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.00001656684,0.0000159717,0.002061715,0.00001884561,0.000005102891,0.00009747624,0.02293818,0.0004103813,0.0001672689,0.9633732,0.001593105,0.009302118],"study_design_scores_gemma":[0.00001249346,0.00001493528,0.002648547,0.00006477061,0.000004657532,0.0001131485,0.02427305,0.001681647,0.0002700526,0.9041216,0.06678151,0.00001348957],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5532768,0.005008948,0.02813117,0.09415336,0.0003586578,0.00003390399,0.00008338468,0.00004133652,0.3189125],"genre_scores_gemma":[0.9950579,0.0005163079,0.0009533665,0.0006384421,0.00007534421,0.000006585594,0.000009316619,0.00001467727,0.002728026],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006028429,"threshold_uncertainty_score":0.02083254,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03272774213986448,"score_gpt":0.2681070153199638,"score_spread":0.2353792731800993,"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."}}