{"id":"W1658553765","doi":"10.24908/ss.v8i2.3486","title":"Empowerment: Analyzing Technologies of Multiple Variable Visibility","year":2010,"lang":"en","type":"article","venue":"Surveillance & Society","topic":"Privacy, Security, and Data Protection","field":"Social Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Visibility; Empowerment; Plural; Context (archaeology); Representation (politics); Process (computing); Power (physics); Emerging technologies; Public relations; Variable (mathematics); Sociology; Computer science; Business; Political science; Law; Geography; Artificial intelligence; Linguistics","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":[0.002539907,0.0001109391,0.000215849,0.00002466623,0.0005322009,0.00005391174,0.0005887185,0.0002643484,0.0001423361],"category_scores_gemma":[0.002736505,0.0001086601,0.0001452342,0.000574657,0.0006031095,0.0002841244,0.000274858,0.0003780783,0.000009781756],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007368152,"about_ca_system_score_gemma":0.0001590896,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005458168,"about_ca_topic_score_gemma":0.006709868,"domain_scores_codex":[0.9986579,0.0001173525,0.0002451001,0.0003279762,0.0003018859,0.0003497236],"domain_scores_gemma":[0.9987642,0.0002198905,0.0001636654,0.0006201208,0.0001826154,0.00004957037],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002606495,0.0002249715,0.9273163,0.00008583094,0.00006242915,5.960558e-7,0.01101089,0.000005235677,0.0375382,0.007087021,0.006210393,0.01043205],"study_design_scores_gemma":[0.002354346,0.0001866954,0.2998381,0.00006797127,0.00003832732,0.000004532162,0.05231924,0.001791361,0.01878781,0.1035305,0.5195675,0.001513653],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9859818,0.0004002186,0.004023156,0.001082103,0.0009916725,0.0004647896,0.0001033566,0.000586581,0.006366293],"genre_scores_gemma":[0.9937745,0.0003915035,0.0055874,0.00002571605,0.0001116847,0.00001603283,0.00001624026,0.000007583185,0.00006934678],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6274782,"threshold_uncertainty_score":0.8251154,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01472357293673462,"score_gpt":0.2885201557357163,"score_spread":0.2737965827989817,"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."}}