Risk Factors Affecting Public Infrastructure Projects
Bibliographic record
Abstract
The delivery of public infrastructure projects in South Africa is bedevilled with many challenges leading to project delays and loss of needed public resources. This study, therefore, sought to identify the risk factors affecting project delivery and the sources of these risk factors. This study employs a qualitative research methodology. To gather the required data, open-ended interview questions were administered to the participants from the various provincial departments in the Northern Cape responsible for delivering public infrastructure construction projects. A purposive sampling technique was used to select the relevant participants to form part of the study. The data collected were analysed using qualitative content analysis. The underpinning factors for these risks affecting project execution are classified as internally and externally generated. The identified risk factors pose a significant threat to project delivery leading to delay and loss of public funds and adequate service delivery to the public. This study helps us understand the risk factors and their source for public infrastructure construction projects. The government and departments in the Northern Cape and other provinces can take measures to tackle these risk factors and alleviate their negative impact on project delivery.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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; both teacher heads agree on what is shown here.
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".