A risk management model for large projects in the construction phase in Egypt
Bibliographic record
Abstract
The implementation of major projects is complicated by the multiplicity of beneficiaries, owners, and all participants in the project as well as the technical overlap between the various engineering, financial and administrative works, while the specific features of the construction activity have a clear influence in shaping the nature of construction projects because the implementation processes were associated with a deep and long-term intervention in the natural environment, where construction is a burden on the environment, both in the construction phase and during the maintenance and liquidation phases: it requires depreciation of a large number of material resources. Through that, this study focused on clarifying the most important concepts of risk management and modern strategies in risk analysis and how to respond to them and monitor projects. The study then presented a questionnaire for the risks facing major projects in Egypt. Through analyzing the results of the questionnaire, a qualitative risk analysis was conducted that can be used to prioritize response to risks, in addition to conducting a Monte Carlo simulation based on theoretical foundations and providing a new process for prioritizing project risks related to sustainability, where the (Primavera Risk Analysis) program was used to clarify the impact of risks on project time and cost. All analyses are based on the theoretical background regarding risk, risk management process, and project life cycle approach in the sustainable construction sector. with the help of this study, it is possible to address ways of mitigating the harmful effects on the environment through the implementation of sustainable management in the planning of future projects and better management of current projects.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".