Case Studies for the Planning and Monitoring of Unit- and Fixed-Price Contracts Using Project Scheduling Software
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Scheduling software used for construction projects is generally designed to plan and monitor activities and resources. These types of software allocate resources to the different activities and allow for resource levelling, costing and cash flow calculations. These features are well-adapted to subcontractors who manage their own human and material resource, and allocate them to the activities of one or a multitude of projects. General contractors and consultants do not generally have full control over project resources and, therefore, most software does not directly address their needs for monitoring unit- or fixed-price contracts. In addition, subcontractors' schedule structures do not necessarily follow the logic of the Bill of Quantities which makes it more difficult to monitor financial progress and cash flow. This paper exposes the problems and limitations associated with the existing scheduling software and presents three scheduling solutions using MS-Project and Excel individually or in combination. These methods have been applied to several case studies in irrigation and fisheries mega-infrastructure projects in Morocco and Burkina Faso. The methodology and proposed solutions are validated through their applications on these mega-projects.
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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 | 0.001 |
| 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 it