{"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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.003445823,0.0002850057,0.0004060281,0.00003453273,0.001892251,0.0002859616,0.0003411878,0.0002222977,0.000365458],"category_scores_gemma":[0.0001616795,0.00021155,0.0001351274,0.0003768985,0.0004831443,0.0003157218,0.0001018734,0.0003072503,0.00004884466],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001436746,"about_ca_system_score_gemma":0.00008952249,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.009574278,"about_ca_topic_score_gemma":0.363413,"domain_scores_codex":[0.9971299,0.0006276479,0.0004028424,0.0007319909,0.0005534989,0.0005540926],"domain_scores_gemma":[0.9983624,0.0003765698,0.0001626375,0.0005756742,0.0003309402,0.0001918011],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003360076,0.0001050908,0.7844339,0.00008113446,0.00009058279,8.469532e-7,0.1051442,0.00001042594,0.0004169187,0.09112818,0.01666197,0.001893186],"study_design_scores_gemma":[0.0004332548,0.0001382309,0.6006405,0.00001679369,0.00000314617,9.395073e-7,0.00438504,0.00007174652,0.0000123807,0.004925583,0.3889706,0.0004018129],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9815691,0.00116125,0.00007391642,0.004060382,0.000472059,0.0009423653,0.00004367729,0.0001350506,0.01154219],"genre_scores_gemma":[0.9959216,0.0006645054,0.00008952127,0.0005431047,0.0004820607,0.00003626297,0.00003941527,0.00002307549,0.00220053],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3723086,"threshold_uncertainty_score":0.9994072,"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."}}