Determine the Most Important Construction Risks and Know the Degree of Their Impact on Construction Projects in Iraq
Bibliographic record
Abstract
By performing the Statistical Package for Social Sciences (SPSS) V26 and statistical analysis, this study aims to identify, evaluate and examine risk variables that may impact construction projects in Iraq.The reliability and internal consistency of the factors were tested using Cronbach's alpha coefficient, where Cronbach's alpha for this research was in the range of 0.923, which provides a strong indicator of the validity and reliability of the questionnaire.The relative importance index will be used to measure the degree of these risks.Field, personal and survey interviews were used to obtain these data.The survey consists of two components, the first of which is a sample of general information, and the second part discusses the possibility of risks occurring, having an impact, and the identification of 44 factors.The census results showed, by analyzing the responses from 44 workers, that only 15 factors significantly impacted the occurrence of risks in construction projects in Iraq.These factors affected the project objectives in terms of cost, time and quality, which led to the project not being completed on time.In addition to increase the cost of construction due to failure to take risks into account.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".