{"id":"W2585968287","doi":"","title":"Big Brother’s shadow: Decline in reported use of electronic surveillance by Canadian Federal Law Enforcement","year":2013,"lang":"en","type":"article","venue":"eYLS (Yale Law School)","topic":"European Criminal Justice and Data Protection","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Law enforcement; Government (linguistics); Shadow (psychology); Law; Legislation; Politics; Enforcement; Political science; Electronic surveillance; Federal election; Public administration","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008090071,0.0001354886,0.0001949263,0.00006768588,0.0003360104,0.0002204254,0.0002536214,0.00009957804,0.0009668496],"category_scores_gemma":[0.0003694973,0.0001390691,0.00004837014,0.0002705808,0.0001726029,0.0005324034,0.00004486011,0.0002647256,0.000207694],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003746263,"about_ca_system_score_gemma":0.0004119764,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9882633,"about_ca_topic_score_gemma":0.9930582,"domain_scores_codex":[0.9980342,0.000275263,0.0004271526,0.0002983487,0.0003338641,0.0006312074],"domain_scores_gemma":[0.9989926,0.00009513296,0.0001603611,0.0003129868,0.0001345379,0.000304347],"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":[0.0002679628,0.0004479729,0.09193566,0.00020311,0.0001839185,0.0001149219,0.003536798,0.0003012536,0.01214749,0.8113054,0.06061735,0.01893816],"study_design_scores_gemma":[0.0005004599,0.0001532607,0.004947041,0.00005011697,0.00001332543,0.000003043974,0.0008503684,0.00008006623,0.0006812984,0.001234172,0.991184,0.0003028451],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9192501,0.0004290841,0.0002267204,0.002271591,0.0004504883,0.001246466,0.00009410061,0.0001093384,0.07592211],"genre_scores_gemma":[0.9953334,0.0001763878,0.0001168268,0.00206036,0.000156484,0.00003755647,0.00007147893,0.00002008719,0.002027441],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9305667,"threshold_uncertainty_score":0.9999464,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03397504766286177,"score_gpt":0.2758595922204039,"score_spread":0.2418845445575421,"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."}}