{"id":"W1606438480","doi":"10.31269/triplec.v10i1.305","title":"Persona Rights for User-Generated Content: A Normative Framework for Privacy and Intellectual Property Regulation","year":2012,"lang":"en","type":"article","venue":"tripleC Communication Capitalism & Critique Open Access Journal for a Global Sustainable Information Society","topic":"Privacy, Security, and Data Protection","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Persona; Intellectual property; Normative; Property rights; Internet privacy; Identity (music); Sociology; Perspective (graphical); Political science; Law and economics; User-generated content; Conceptual framework; Business; Law; Computer science; Social media; Aesthetics; Social science; Philosophy; Human–computer interaction; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0350931,0.0008300217,0.0009481031,0.003972296,0.01037165,0.01892179,0.003999013,0.01418152,0.005369129],"category_scores_gemma":[0.03642276,0.0007545167,0.001473819,0.002524357,0.09716871,0.02392817,0.009734959,0.01165141,0.001295361],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01465459,"about_ca_system_score_gemma":0.02011299,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02024501,"about_ca_topic_score_gemma":0.009830101,"domain_scores_codex":[0.963724,0.01912471,0.001575252,0.003811405,0.009482996,0.002281639],"domain_scores_gemma":[0.9672106,0.0190682,0.002008463,0.004591785,0.005787061,0.001333896],"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":[9.750418e-7,0.000001969736,0.00001939569,0.00000402929,5.76407e-7,0.000008605718,0.0007754282,0.00005392061,0.00001671329,0.998512,0.0002170507,0.0003893673],"study_design_scores_gemma":[0.000006878382,0.000005960021,0.00006336727,0.0000981647,0.000003808768,0.00004903531,0.001012353,0.000560378,0.000176927,0.9628607,0.03514715,0.00001528735],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01497143,0.002447306,0.2898554,0.116385,0.0007634204,0.000226376,0.0001742254,0.000203379,0.5749736],"genre_scores_gemma":[0.8943003,0.001759766,0.05715677,0.0151804,0.0008960045,0.0009868295,0.0001526795,0.0002440826,0.02932326],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0350931,"threshold_uncertainty_score":0.1855922,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09671642985209666,"score_gpt":0.4233724763713146,"score_spread":0.326656046519218,"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."}}