{"id":"W3171122582","doi":"","title":"Terms of Silence: Weaknesses in Corporate and Law Enforcement Responses to Cyberviolence against Girls","year":2017,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Hate Speech and Cyberbullying Detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Redress; Silence; Deference; Enforcement; Political science; Social media; Law enforcement; Identity (music); Order (exchange); Public relations; Law; Sociology; Business","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00158992,0.0001330298,0.0001856578,0.0001537601,0.0003802574,0.0002602871,0.0008913071,0.00005246825,0.000002925858],"category_scores_gemma":[0.0001078558,0.0001165799,0.0000404768,0.0001368264,0.00009071534,0.0006455555,0.000206663,0.0005507353,0.000009186808],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001913822,"about_ca_system_score_gemma":0.0005114858,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004013489,"about_ca_topic_score_gemma":0.0008582001,"domain_scores_codex":[0.9980655,0.00008010647,0.0002992385,0.0002545196,0.0002690785,0.001031527],"domain_scores_gemma":[0.998938,0.0000380459,0.0003880031,0.000458585,0.00007118593,0.0001062143],"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":[0.0001945274,0.00007590105,0.01597313,0.00002186286,0.0000430506,0.00004654631,0.0006804826,0.0001748796,0.02871883,0.744524,0.00001532559,0.2095314],"study_design_scores_gemma":[0.003454932,0.003630327,0.09428297,0.001134588,0.00003130052,0.001182043,0.001241977,0.002939744,0.1187037,0.7696155,0.002548394,0.001234518],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9796934,0.000328674,0.01695587,0.0005750235,0.0002271505,0.0001480659,0.000001227508,0.00002156925,0.002049083],"genre_scores_gemma":[0.9969198,0.001794905,0.0007431993,0.0001211401,0.00005351155,0.000006880746,2.399582e-7,0.000007035379,0.0003533103],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2082969,"threshold_uncertainty_score":0.4753991,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01536050610470249,"score_gpt":0.2552714916416871,"score_spread":0.2399109855369846,"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."}}