{"id":"W4393978206","doi":"10.1108/itp-07-2022-0516","title":"Reducing data privacy breaches: an empirical study of relevant antecedents and an outcome","year":2024,"lang":"en","type":"article","venue":"Information Technology and People","topic":"Privacy, Security, and Data Protection","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Brock University","funders":"","keywords":"Business; Outcome (game theory); Information privacy; Internet privacy; Empirical research; Data breach; Knowledge management; Computer science; Economics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008806529,0.00007411416,0.0001333026,0.0003861894,0.0003347495,0.0001374551,0.0004743107,0.0001805026,0.00001342176],"category_scores_gemma":[0.0005076487,0.00006794321,0.00000704305,0.0005072818,0.0001446757,0.003716134,0.0004817114,0.0002065186,0.000006874133],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001960002,"about_ca_system_score_gemma":0.00005495,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002453944,"about_ca_topic_score_gemma":0.002552791,"domain_scores_codex":[0.999137,0.00007326467,0.0003067676,0.0001848865,0.0001622,0.0001358725],"domain_scores_gemma":[0.9992676,0.00004086719,0.00007997131,0.000513399,0.00004365557,0.00005448247],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00005592514,0.0003931966,0.344865,0.0002430478,0.00005002858,0.000003071598,0.345593,0.000001728342,0.00009911806,0.008705822,0.0007970179,0.2991931],"study_design_scores_gemma":[0.002230317,0.002877785,0.2905525,0.0001907753,0.0001880086,0.0001140652,0.5322556,0.02225495,0.0004021026,0.05087931,0.09715106,0.0009034678],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9962072,0.0001359375,0.00113883,0.001495018,0.0001606896,0.0003335391,0.00005064258,0.0002745829,0.0002035343],"genre_scores_gemma":[0.9992324,0.0001486753,0.0004362401,0.00003241494,0.0000388261,0.00001147097,0.00008795227,0.000003277714,0.000008749702],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2982896,"threshold_uncertainty_score":0.3709646,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0636896574793344,"score_gpt":0.3936965556341249,"score_spread":0.3300068981547905,"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."}}