The Significance of Project Manager Competencies in Recruitment: A Means of Supporting Success in the Construction Industry
Bibliographic record
Abstract
Given the dynamic nature of construction, evolving standards, principles, and methodologies introduce new considerations in the delivery of construction projects.A project manager plays a pivotal role in ensuring overall project success by effectively overseeing project execution in light of these potentially conflicting factors.As such, there is increasing interest in identifying and exploring project manager competencies that existing literature does not address specifically in the Canadian construction sector.The purpose of this paper is (1) to identify and analyze competencies desired for construction project managers, and (2) to understand the correlation between competencies, in addition to how contracting parties (owner, consultant, and contractor) and industries (building, infrastructure, and industrial) influence these competencies.A literature review was completed to develop a competency framework.220 Albertan job advertisements were reviewed and competencies were recorded.The frequency and phi coefficient of each competency was calculated for all postings, then for postings specific to each contracting party and type of industry.The Fisher-Freeman Halton test was employed to determine dependency of competency frequency on contracting party and industry.Technical, communication, and select managerial and financial competencies were highly cited.Owner and consultant postings favoured technical and communication competencies while contractor postings included communication and select managerial competencies.There is less variation in competency citation frequency between industries and positive relationships were observed between oral and written communication competencies.Desired competencies are influenced by the services to be provided, the industry in which work will take place, and other competencies included in the postings.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.022 | 0.058 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".