{"id":"W2999460696","doi":"10.24908/ss.v17i3/4.10779","title":"Humanitarian and Human Rights Surveillance: The Challenge to Border Surveillance and Invisibility?","year":2019,"lang":"en","type":"article","venue":"Surveillance & Society","topic":"Migration, Refugees, and Integration","field":"Social Sciences","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Human rights; Political science; Humanitarian aid; European union; International humanitarian law; Computer security; Law; Business; International trade; Computer science","routes":{"ca_aff":true,"ca_fund":true,"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":[0.01280531,0.0004775993,0.0005311015,0.001620959,0.004883234,0.01445047,0.001284711,0.004893858,0.002817402],"category_scores_gemma":[0.01457653,0.0002429698,0.0004612133,0.00160755,0.04102465,0.02211685,0.00836906,0.006487123,0.0004071865],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004448595,"about_ca_system_score_gemma":0.006830541,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006490842,"about_ca_topic_score_gemma":0.003424632,"domain_scores_codex":[0.9861158,0.009582371,0.0004272054,0.0009896981,0.001682955,0.00120203],"domain_scores_gemma":[0.9893214,0.005613408,0.001498229,0.00129584,0.001354638,0.0009165108],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.0000150955,0.0000160788,0.001470018,0.00007223211,0.000005757465,0.00006830006,0.02116766,0.0001586765,0.00009753907,0.9486525,0.003338659,0.02493741],"study_design_scores_gemma":[0.00002674921,0.0001467925,0.007492772,0.001808948,0.00001885292,0.0007452518,0.1368643,0.001175248,0.0003593476,0.5532955,0.2979936,0.00007267176],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.09208093,0.03530974,0.037449,0.5259004,0.003277429,0.00008838128,0.00007815063,0.00008934407,0.3057267],"genre_scores_gemma":[0.9702224,0.006919749,0.003913639,0.01070782,0.001325578,0.00007052791,0.00003731946,0.00003582124,0.006767106],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01445047,"threshold_uncertainty_score":0.06772178,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01138168578368604,"score_gpt":0.3005074484136171,"score_spread":0.2891257626299311,"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."}}