{"id":"W3014620144","doi":"10.1080/01442872.2020.1748264","title":"The problem <i>of</i> innovation in technoscientific capitalism: data <i>rentiership</i> and the policy implications of turning personal digital data into a private asset","year":2020,"lang":"en","type":"article","venue":"Policy Studies","topic":"Digital Economy and Work Transformation","field":"Social Sciences","cited_by":142,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; York University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Capitalism; Asset (computer security); Business; Economics; Political science; Computer science; Law; Computer security","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":["sts"],"domain":null,"study_design":"theoretical_or_conceptual","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":["sts"],"domain":null,"study_design":"theoretical_or_conceptual","genre":"other","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001093757,0.00008263892,0.0001708462,0.000124829,0.0005422191,0.0002052881,0.000873445,0.00002865067,2.908725e-7],"category_scores_gemma":[0.001533958,0.00005413117,0.00001598011,0.002042017,0.001607226,0.001320474,0.0005929621,0.00009520811,9.954663e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003497349,"about_ca_system_score_gemma":0.0002441782,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008670553,"about_ca_topic_score_gemma":0.001160417,"domain_scores_codex":[0.998898,0.00005308022,0.0004735047,0.0002149194,0.0001798261,0.0001806431],"domain_scores_gemma":[0.9989321,0.0003219224,0.0002667024,0.0003315485,0.0001198655,0.00002783714],"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":[0.00003204581,0.00002739002,0.003326238,0.00007365541,0.00007834307,6.058129e-8,0.1223501,0.00000310087,0.00004812293,0.8191572,0.003122503,0.05178121],"study_design_scores_gemma":[0.002091111,0.00007130555,0.003595068,0.0002018943,0.00007402112,0.000001655633,0.195389,0.000902597,0.0002228437,0.2921732,0.5048509,0.0004264743],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.4039773,0.004273816,0.0008891752,0.5584428,0.0001114434,0.001970391,0.001585659,0.0001006617,0.02864875],"genre_scores_gemma":[0.9984407,0.0008148871,0.0001097367,0.0003244106,0.00009478271,0.00002347193,0.0001522858,0.000004317954,0.00003537913],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5944634,"threshold_uncertainty_score":0.5921891,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09359972695168417,"score_gpt":0.3592215109544058,"score_spread":0.2656217840027216,"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."}}