{"id":"W4417335878","doi":"10.36871/ek.up.p.r.2025.12.01.022","title":"ETHICAL PROBLEMS OF DIGITAL TRANSFORMATION OF PUBLIC ADMINISTRATION IN RUSSIA AND POSSIBLE SOLUTIONS","year":2025,"lang":"","type":"article","venue":"EKONOMIKA I UPRAVLENIE PROBLEMY RESHENIYA","topic":"Security, Politics, and Digital Transformation","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Transparency (behavior); Digital transformation; Legislation; Digital rights; Process (computing); Digital economy; Fundamental rights; State (computer science)","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002404782,0.0003889561,0.0007429683,0.0008883475,0.0004133338,0.0005606417,0.0004271682,0.0009042353,0.00005421005],"category_scores_gemma":[0.0005095575,0.0004316831,0.0002403674,0.001081467,0.001634775,0.003380004,0.00009171405,0.0007650736,0.000008092396],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002951087,"about_ca_system_score_gemma":0.002197269,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004183881,"about_ca_topic_score_gemma":0.002629919,"domain_scores_codex":[0.9951216,0.0003988707,0.002421802,0.000518916,0.0006207933,0.0009180222],"domain_scores_gemma":[0.9979671,0.0004405401,0.0005878604,0.000320119,0.0004082244,0.000276163],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00018921,0.0008636645,0.01364529,0.002409605,0.000102371,6.475682e-7,0.02864095,0.00006882304,0.0002104603,0.9386789,0.00008456283,0.01510556],"study_design_scores_gemma":[0.01337608,0.00294487,0.06091091,0.005175212,0.0005822695,0.0000234592,0.0563701,0.01347277,0.008344836,0.8044642,0.03181754,0.002517725],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6329964,0.002980511,0.00664911,0.02873832,0.0006616733,0.003796414,0.0005930156,0.0001086291,0.3234759],"genre_scores_gemma":[0.9978492,0.001335923,0.0001731436,0.00008003693,0.00005777155,0.00007749664,0.000118567,0.00001904455,0.0002887926],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3648528,"threshold_uncertainty_score":0.9998135,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05514512427705658,"score_gpt":0.3208137630954963,"score_spread":0.2656686388184397,"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."}}