{"id":"W4412822424","doi":"10.1504/ijwi.2025.147772","title":"Unravelling the project escalation enigma: optimising principal-agent dynamics in IT project management","year":2025,"lang":"en","type":"article","venue":"International Journal of Work Innovation","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mount Royal University; Université Laval","funders":"","keywords":"Principal (computer security); De-escalation; Dynamics (music); Process management; Project management; Computer science; Operations research; Engineering management; Management science; Knowledge management; Operations management; Business; Engineering; Systems engineering; Political science; Sociology; Computer security","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.005531948,0.001011083,0.0009550096,0.0007432019,0.000976964,0.005000495,0.00110843,0.001645176,0.001881828],"category_scores_gemma":[0.0187893,0.000741672,0.0005568622,0.0005313329,0.003532335,0.006163694,0.003830958,0.002615795,0.0003176114],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001198102,"about_ca_system_score_gemma":0.003223589,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001831339,"about_ca_topic_score_gemma":0.001819211,"domain_scores_codex":[0.9978516,0.001431789,0.00007640191,0.000262973,0.0001904595,0.0001868823],"domain_scores_gemma":[0.9917409,0.005734112,0.001267012,0.0003734472,0.0003987574,0.0004856771],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001895628,0.0001729832,0.006845632,0.0004898609,0.0001563193,0.0002572825,0.002364767,0.6805695,0.002511583,0.2180614,0.002081749,0.08629944],"study_design_scores_gemma":[0.00003499647,0.0001471692,0.0007629014,0.0001011827,0.00002856389,0.00004373458,0.0007849581,0.7985306,0.000432491,0.1954722,0.003627044,0.00003404903],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1137184,0.003405888,0.860955,0.01021675,0.000209393,0.0001215457,0.00003715212,0.0001885613,0.0111474],"genre_scores_gemma":[0.9264235,0.001380902,0.07056227,0.0002123267,0.0000788307,0.00009730468,0.00002017555,0.00004567447,0.001178912],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005531948,"threshold_uncertainty_score":0.02925611,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06435953035890153,"score_gpt":0.3406154004366568,"score_spread":0.2762558700777553,"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."}}