{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006340093,0.0004910216,0.0004266046,0.003803507,0.003061026,0.008220871,0.0008286226,0.001612304,0.005521918],"category_scores_gemma":[0.01960709,0.0003633453,0.0008657009,0.003959721,0.01359603,0.01826364,0.007965092,0.002355637,0.0004672102],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002177364,"about_ca_system_score_gemma":0.001430274,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006506714,"about_ca_topic_score_gemma":0.0002967604,"domain_scores_codex":[0.9931294,0.004119862,0.000203154,0.0006952378,0.001159102,0.0006930799],"domain_scores_gemma":[0.9724266,0.02101449,0.002796785,0.002287271,0.0009261139,0.0005487863],"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":[0.00003284383,0.00004402352,0.004338008,0.0001132298,0.00001332909,0.0003144982,0.01565846,0.001017748,0.0004680114,0.9592515,0.0003664443,0.01838202],"study_design_scores_gemma":[0.00003963612,0.0001678969,0.005927782,0.0004316184,0.00005220772,0.001349916,0.04839241,0.01164176,0.002822123,0.8510744,0.07803907,0.00006116055],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.3708704,0.004760476,0.3508012,0.007937282,0.0002237624,0.0005218559,0.0002515234,0.000135699,0.2644977],"genre_scores_gemma":[0.9716823,0.001498064,0.02230456,0.0001666933,0.00006720678,0.0003230189,0.00005991283,0.00003449539,0.003863811],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008220871,"threshold_uncertainty_score":0.03353,"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."}}