{"id":"W4379134727","doi":"10.2139/ssrn.4464300","title":"Weaponizing Privacy and Copyright Law for Censorship","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Freedom of Expression and Defamation","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Centre for International Governance Innovation","funders":"","keywords":"Intellectual property; Government (linguistics); Censorship; Privacy laws of the United States; Journalism; Internet privacy; The Internet; Business; Political science; Information privacy; Public relations; Law; Computer science","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":[],"consensus_categories":[],"category_scores_codex":[0.002655433,0.00006521646,0.00009121886,0.00007535344,0.001051131,0.0001338321,0.0001561632,0.00006875608,0.00003237591],"category_scores_gemma":[0.0002847998,0.00005589808,0.00005315948,0.0001792776,0.0001076825,0.000271865,0.00002062151,0.0004001877,0.00003957971],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000220565,"about_ca_system_score_gemma":0.0005833568,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00019206,"about_ca_topic_score_gemma":0.002098543,"domain_scores_codex":[0.9981242,0.0001075515,0.0001411927,0.0001146169,0.0002315131,0.001280896],"domain_scores_gemma":[0.999501,0.0001868552,0.00007947841,0.00006291797,0.00006909376,0.0001006673],"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":[0.00002294441,0.000007163708,0.0001131356,0.000003390991,0.00001234851,6.407139e-7,0.001959278,0.00000241931,0.0004466691,0.9914955,0.002144992,0.003791475],"study_design_scores_gemma":[0.0005550182,0.00008048028,0.0001359733,0.00002300929,0.00001044562,0.00001331644,0.007434702,0.0001424897,0.0001551974,0.8020219,0.1893169,0.0001105856],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8237935,0.005423353,0.01081215,0.0500669,0.002327302,0.001253286,0.00001072507,0.0007225426,0.1055902],"genre_scores_gemma":[0.9913649,0.001714066,0.0001947187,0.0001618894,0.0005113471,0.0000073272,0.000002780704,0.00001118465,0.006031805],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1894736,"threshold_uncertainty_score":0.8084558,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03199122670154732,"score_gpt":0.3265038156213679,"score_spread":0.2945125889198206,"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."}}