{"id":"W6906784493","doi":"10.18280/ijsdp.200631","title":"Legal Challenges of Using AI and Big Data in Public Administration: Administrative Liability, Data Protection, and Public Services Efficiency","year":2025,"lang":"en","type":"article","venue":"International Journal of Sustainable Development and Planning","topic":"Ethics and Social Impacts of AI","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Big data; Services computing; Administrative services organization; Public sector; Data Protection Act 1998","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.08574957,0.0004083311,0.0007974257,0.008174731,0.00405853,0.02098138,0.002136667,0.003491448,0.001943941],"category_scores_gemma":[0.224523,0.000625578,0.0009401593,0.009701424,0.01207468,0.02067174,0.009141388,0.005350354,0.0002894094],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008675863,"about_ca_system_score_gemma":0.01519863,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006339952,"about_ca_topic_score_gemma":0.00689393,"domain_scores_codex":[0.8959771,0.06526183,0.006288352,0.005119803,0.02438008,0.002972863],"domain_scores_gemma":[0.6173372,0.2965302,0.04232555,0.01929671,0.02153369,0.00297667],"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":[0.0002230023,0.0002677096,0.1520577,0.001377222,0.0003209577,0.0009181357,0.01353126,0.01721977,0.001762403,0.592426,0.006283765,0.213612],"study_design_scores_gemma":[0.00005672491,0.0003383115,0.1046729,0.00514963,0.0002674031,0.001893287,0.04263903,0.06817859,0.00662993,0.6658006,0.1040848,0.0002888303],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5366433,0.01585541,0.2043133,0.144973,0.0004678973,0.0006710657,0.001118597,0.0002322629,0.09572514],"genre_scores_gemma":[0.9711654,0.0021094,0.02308886,0.002220296,0.0002141203,0.0001670228,0.0002182964,0.00004269796,0.0007738397],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08574957,"threshold_uncertainty_score":0.4534925,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1956883681715087,"score_gpt":0.4182588714263634,"score_spread":0.2225705032548547,"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."}}