Classification of Risks for International Construction Joint Ventures (ICJV) Projects
Bibliographic record
Abstract
Several (ICJVs) have failed achieving time, cost and quality targets because of lack of an appropriate risk assessment methodology. This paper focuses on the analysis of the different ICJV risk environments. The related risks are analyzed into country, operating, sociopolitical and financial risks and then identified and grouped into internal, project specific, schedules, and major contract clauses risks. A simplified decision support system (RAMSCO) is proposed that breaks down project risks into discrete phases systematically. At each completion phase, there is a decision point where the up-date risk assessment can be reviewed and forth-coming actions can be identified giving the user a decision milestone whether to proceed or not. RAMSCO directs users through indices to minimize ICJV failure chances and evaluates the project's overall risk based on factor weighted ratings obtained from published researches. Two case studies are used to demonstrate RAMSCO's potential value.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".