{"id":"W3187516375","doi":"10.2139/ssrn.3857360","title":"Home Ice Advantage: Securing Data Sovereignty for Canadians on Social Media","year":2020,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Privacy, Security, and Data Protection","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University; University of Ottawa","funders":"","keywords":"Sovereignty; Social media; Political science; Business; Internet privacy; Computer security; Computer science; Law; Politics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008828738,0.0002868634,0.0003643569,0.002304463,0.01493513,0.01107386,0.002141568,0.003666066,0.01583729],"category_scores_gemma":[0.03742263,0.0003550143,0.0004594005,0.003072187,0.005559987,0.006007086,0.005951044,0.003837415,0.001414309],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03847689,"about_ca_system_score_gemma":0.1524796,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9674431,"about_ca_topic_score_gemma":0.9727448,"domain_scores_codex":[0.9915313,0.0009620914,0.0001830261,0.0006094584,0.003243756,0.003470514],"domain_scores_gemma":[0.9749119,0.006761962,0.001133633,0.002880416,0.01047292,0.003839194],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004759833,0.0001873678,0.07948475,0.0001440501,0.00005811541,0.0007285525,0.01900155,0.001795226,0.001064209,0.4711283,0.2917272,0.1342046],"study_design_scores_gemma":[0.0002349467,0.0001845887,0.08015388,0.0005737278,0.0001800358,0.0003213438,0.05543095,0.01166492,0.004591151,0.06683571,0.7795116,0.0003170647],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2540243,0.0008515147,0.01005814,0.05996703,0.0005111301,0.0005357456,0.003489651,0.001009731,0.6695528],"genre_scores_gemma":[0.9212487,0.000420653,0.006882857,0.007328214,0.0001242547,0.0001410645,0.001058071,0.0001624746,0.06263364],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03847689,"threshold_uncertainty_score":0.2791706,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04566877208316365,"score_gpt":0.311999073670044,"score_spread":0.2663303015868803,"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."}}