{"id":"W2272073777","doi":"","title":"To Observe and Protect? How Digital Rights Management Systems Threaten Privacy and What Policy Makers Should Do About it","year":2008,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Digital Rights Management and Security","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Business; Internet privacy; License; Personally identifiable information; Digital rights management; Data Protection Act 1998; Computer security; Anonymity; Privacy policy; Privacy law; Control (management); Information privacy; Law and economics; Law; Political science; Computer science; Economics","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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0005150943,0.000295367,0.0002732204,0.0003333484,0.000482304,0.005373515,0.0008343989,0.0000671715,9.373827e-7],"category_scores_gemma":[0.00001537094,0.000216676,0.00007802666,0.0004227639,0.00008406748,0.005468858,0.0005430796,0.0005952126,0.00001655016],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003960937,"about_ca_system_score_gemma":0.0002245728,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004575551,"about_ca_topic_score_gemma":0.00006323634,"domain_scores_codex":[0.9968507,0.00004522646,0.0002705482,0.0005192806,0.0005477081,0.001766518],"domain_scores_gemma":[0.9990934,0.00002508515,0.0001365303,0.0004000178,0.00006942745,0.0002755425],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00003418596,0.00007588205,0.0004774252,0.00004526149,0.0002666852,0.0001539234,0.001179538,0.00001513144,0.000003714318,0.9145511,0.0004814795,0.08271569],"study_design_scores_gemma":[0.002787292,0.001408759,0.005801804,0.0005450897,0.00006523351,0.003208841,0.00224595,0.001668814,0.00004184403,0.8400528,0.1407968,0.001376741],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8339278,0.01469668,0.09939271,0.02836618,0.000738731,0.003104884,0.000005783362,0.0003669321,0.01940035],"genre_scores_gemma":[0.9854926,0.006907592,0.0002573561,0.0001977525,0.0001820926,0.00002534819,0.000001686213,0.00001704485,0.006918568],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1515648,"threshold_uncertainty_score":0.995659,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02113237457386825,"score_gpt":0.2377065315590628,"score_spread":0.2165741569851946,"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."}}