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Record W1999557334 · doi:10.1108/14635770310457520

A multi‐level causal model for best practices in project management

2003· article· en· W1999557334 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBenchmarking An International Journal · 2003
Typearticle
Languageen
FieldDecision Sciences
TopicConstruction Project Management and Performance
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsModerationInterpersonal communicationProject managementKnowledge managementOPM3PsychologyOutcome (game theory)Best practiceCausal modelSocial skillsProject management triangleProcess managementConflict managementComputer scienceBusinessEngineeringSocial psychologyManagementPolitical scienceMedicine

Abstract

fetched live from OpenAlex

This paper presents a multi‐level causal model for best practices in project management based upon the literature, especially empirical studies of competencies and project management. The model emphasizes the roles of technical project management skills and interpersonal or people skills as inputs to the model. Next, the model stresses the important roles of organizational facilitators and inhibitors, that is, moderator variables (e.g. project management systems and supportive senior management) in influencing project outcomes. The model addresses the outcome variables of technical competencies (e.g. planning and controlling) and people competencies (e.g. interpersonal communication and conflict management skills). Finally, the model recognizes the important role of feedback for corrective actions and reinforcing best practices, that is, organizational learning.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.823
Threshold uncertainty score0.945

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.450
GPT teacher head0.501
Teacher spread0.051 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it