A framework for estimating the total cost of buried municipal infrastructure renewal projects
Bibliographic record
Abstract
As Canadian municipalities venture into rehabilitation and replacement of extensively deteriorated underground water distribution and sewerage assets, municipal decision-makers, engineering and construction research bodies and the public all feel that this type of construction work can have adverse effects on the society. This thesis reviews these negative impacts which include, but are not limited to damage of nearby buried and above-ground infrastructure, disruption of traffic, loss of accessibility to businesses, health hazards to workers and the public, and finally environmental pollution and damage. There is presently no accepted practice-oriented method for the evaluation of these social, economic and environmental impacts. This research project proposes a framework to enable municipalities, utility agencies and contracting firms to quantitatively estimate the total cost to society of buried municipal infrastructure renewal projects using open trench, or trenchless construction methods. The total cost of a project is the sum of all the direct and indirect costs borne by the client organization, and external costs borne by society. The external costs can be separated into three components: social, economic and environmental costs. Use of the proposed methodology in a case study of a water main rehabilitation project using trenchless technologies in the city of Montreal, Canada, revealed that the indirect and external costs of the project were approximately 25 percent of its direct costs. The most significant cost components were those attributable to increased vehicular travel time and lost business income.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".