{"id":"W4372215941","doi":"10.1145/3572334.3572387","title":"Son Mis Datos: Building Personal Data Literacies through Citizen Data Audits","year":2022,"lang":"en","type":"article","venue":"","topic":"Privacy, Security, and Data Protection","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Audit; Data access; Public relations; Data sharing; Open data; Business; Internet privacy; Computer science; Political science; World Wide Web; Accounting; Database","routes":{"ca_aff":true,"ca_fund":true,"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":[0.02166597,0.0005508764,0.0003233005,0.002364778,0.002751453,0.004772986,0.001238935,0.0007967486,0.004403914],"category_scores_gemma":[0.0326032,0.0005845908,0.0003362957,0.001581084,0.004902962,0.008005979,0.01175517,0.001832802,0.0009219017],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002616688,"about_ca_system_score_gemma":0.009178157,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006666768,"about_ca_topic_score_gemma":0.008351824,"domain_scores_codex":[0.9815664,0.01400551,0.0004441654,0.001103883,0.002153756,0.0007263383],"domain_scores_gemma":[0.9587203,0.02013776,0.002895914,0.01051625,0.005555806,0.002173997],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0006328067,0.002894783,0.1139005,0.0008512206,0.00005858508,0.0007557968,0.2418714,0.002859562,0.01173289,0.05179097,0.01633741,0.5563142],"study_design_scores_gemma":[0.0004108335,0.003038291,0.07573383,0.001293085,0.0001171386,0.0008998635,0.2883266,0.03140758,0.04288985,0.06815532,0.4874432,0.0002843441],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8138021,0.000220618,0.1159685,0.005226885,0.00007999651,0.003566713,0.001125076,0.002997853,0.05701233],"genre_scores_gemma":[0.8621913,0.0002350837,0.1259895,0.0004219377,0.00002187579,0.001801804,0.0010264,0.0002753602,0.008036758],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02166597,"threshold_uncertainty_score":0.114582,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1364795513834114,"score_gpt":0.3770871933089852,"score_spread":0.2406076419255738,"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."}}