{"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":"codex-gemma-dda1882f352a","candidate_categories":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001959026,0.0001307867,0.0001561103,0.00005890771,0.002560077,0.0003847969,0.004749015,0.00005664174,0.004923353],"category_scores_gemma":[0.001242511,0.000135077,0.00002882145,0.0004645053,0.0001793407,0.003354634,0.007775524,0.0003242998,0.00005539024],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001259063,"about_ca_system_score_gemma":0.000260547,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0133747,"about_ca_topic_score_gemma":0.002077039,"domain_scores_codex":[0.9973518,0.0003894094,0.0002147574,0.0007827376,0.0008381633,0.0004231569],"domain_scores_gemma":[0.997666,0.0001660079,0.0001046415,0.001925286,0.00004391954,0.00009416661],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000490654,0.0001966319,0.000983911,0.00004116589,0.00007353844,0.00002352384,0.04355187,0.000002285396,0.0004643098,0.03690644,0.8920184,0.02568889],"study_design_scores_gemma":[0.0002007944,0.00002726483,0.0001519464,0.000009032295,0.00002162518,0.000007640391,0.01822515,0.002009273,0.00004328013,0.00782187,0.9712679,0.0002142591],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2447906,0.01490249,0.08343206,0.1594569,0.01629786,0.005306874,0.07457676,0.004226099,0.3970104],"genre_scores_gemma":[0.9629557,0.000754825,0.01754835,0.002364167,0.00243282,0.00005641717,0.01055728,0.00003877601,0.003291712],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7181651,"threshold_uncertainty_score":0.9987385,"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."}}