{"id":"W3016357568","doi":"","title":"Data is dangerous: comparing the risks that the United States, Canada and Germany see in data troves","year":2020,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Privacy, Security, and Data Protection","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"German; National security; Data Protection Act 1998; Personally identifiable information; Government (linguistics); Business; Political science; Foreign direct investment; Investment (military); Public administration; Law; Politics; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002999085,0.0003568213,0.0003179295,0.004491744,0.009365092,0.008531918,0.001247427,0.001784492,0.00389693],"category_scores_gemma":[0.01495924,0.0002681707,0.0008454399,0.00676077,0.005292611,0.004531036,0.004338115,0.002687307,0.0003735577],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04303102,"about_ca_system_score_gemma":0.03783926,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9755175,"about_ca_topic_score_gemma":0.980412,"domain_scores_codex":[0.9929472,0.0008042407,0.000180202,0.000350943,0.003228684,0.00248869],"domain_scores_gemma":[0.9882267,0.002037734,0.002437637,0.0003565394,0.004639193,0.002302151],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007941161,0.0002169567,0.7004995,0.0002832756,0.0003222045,0.001352893,0.07754669,0.001850221,0.0003471865,0.07960793,0.07079645,0.06638257],"study_design_scores_gemma":[0.00004297095,0.0001069612,0.6554339,0.0008130533,0.0001862156,0.000420375,0.2508491,0.001513884,0.0005036072,0.003797175,0.08611977,0.0002129919],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8650577,0.004418669,0.000440494,0.02498704,0.0001943972,0.00009796947,0.002733583,0.00004114562,0.102029],"genre_scores_gemma":[0.9883907,0.002852432,0.0002051384,0.002953012,0.00003405163,0.00002163154,0.00122998,0.00002614333,0.004286902],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04303102,"threshold_uncertainty_score":0.3122134,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2382392852580004,"score_gpt":0.3960055057467286,"score_spread":0.1577662204887282,"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."}}