{"id":"W1518708590","doi":"10.1108/09565691311325004","title":"Information culture in a government organization","year":2013,"lang":"en","type":"article","venue":"Records Management Journal","topic":"Personal Information Management and User Behavior","field":"Decision Sciences","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Government (linguistics); Data collection; Christian ministry; Management training; Work (physics); Sample (material); Records management; Knowledge management; Perception; Organizational culture; Population; Business; Medical education; Psychology; Public relations; Medicine; Engineering; Management; Political science; Computer science; Sociology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004168352,0.0001153913,0.0001736176,0.001275665,0.00512317,0.005999781,0.0007581955,0.0004527537,0.001911271],"category_scores_gemma":[0.01001976,0.0001483426,0.0001601071,0.002382598,0.00430567,0.001753509,0.002523196,0.0008058913,0.0002973421],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008712241,"about_ca_system_score_gemma":0.01055416,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06399909,"about_ca_topic_score_gemma":0.04228513,"domain_scores_codex":[0.9919513,0.004119194,0.0004755745,0.0004447022,0.002068547,0.0009406395],"domain_scores_gemma":[0.9829029,0.004050694,0.00440943,0.001280899,0.003691504,0.003664603],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.000121837,0.0005102179,0.525169,0.0002714624,0.00009585673,0.0009617864,0.3179459,0.000765609,0.002876952,0.01600891,0.005611124,0.1296614],"study_design_scores_gemma":[0.0000238913,0.0004853171,0.434218,0.0003716656,0.0000387607,0.0007205413,0.4756023,0.0009680043,0.0009917592,0.002363976,0.08414318,0.00007262427],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9704869,0.0003357011,0.0005309964,0.002125914,0.00002339462,0.00002680792,0.00003532613,0.00002588452,0.02640917],"genre_scores_gemma":[0.9983841,0.0001549678,0.000283032,0.0002213331,0.000008189125,0.000007543959,0.00002149459,0.000004615569,0.0009146169],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06399909,"threshold_uncertainty_score":0.1272531,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0631305517403312,"score_gpt":0.3416919148339407,"score_spread":0.2785613630936095,"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."}}