{"id":"W2081455579","doi":"10.5210/fm.v15i1.2775","title":"Aliases, creeping, and wall cleaning: Understanding privacy in the age of Facebook","year":2010,"lang":"en","type":"article","venue":"First Monday","topic":"Privacy, Security, and Data Protection","field":"Social Sciences","cited_by":372,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mainstream; Internet privacy; Personally identifiable information; Information privacy; Privacy policy; Ethnography; Privacy by Design; Privacy software; Business; Sociology; Public relations; Political science; Computer science; Computer security; Law","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005032113,0.000415389,0.0002544008,0.00151637,0.01073419,0.009535461,0.0009510285,0.003127554,0.00296633],"category_scores_gemma":[0.009705387,0.0005022256,0.0003842188,0.0008776501,0.01757945,0.02211328,0.007052006,0.003663517,0.000478011],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004000349,"about_ca_system_score_gemma":0.0023918,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02297327,"about_ca_topic_score_gemma":0.03052943,"domain_scores_codex":[0.9964693,0.002404154,0.00009838629,0.0002368019,0.0003655926,0.0004257937],"domain_scores_gemma":[0.9945503,0.003133802,0.0009694719,0.0004119456,0.0004069149,0.0005275902],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00001498596,0.00001120494,0.007040114,0.00002789578,0.00000399228,0.0002930455,0.955442,0.00003210356,0.0001969819,0.02829259,0.0009912266,0.007653845],"study_design_scores_gemma":[0.000003241904,0.00003063821,0.006335841,0.0001990033,0.00001282142,0.0007441738,0.8821261,0.0002537979,0.0003189394,0.01699634,0.09295554,0.00002349978],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8137667,0.009472336,0.009161573,0.03913001,0.0002330087,0.0000569775,0.0001264799,0.00006091105,0.127992],"genre_scores_gemma":[0.991899,0.00206914,0.0006771969,0.0009918998,0.00003732794,0.00001808095,0.00002355957,0.00001617835,0.004267605],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02297327,"threshold_uncertainty_score":0.04567909,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06693911515126244,"score_gpt":0.3061864419072351,"score_spread":0.2392473267559727,"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."}}