Analyzing Obstacles and Exploring Opportunities to Improve Modular Industrialized Construction in Lebanon
Bibliographic record
Abstract
Over the past few decades, modular concrete construction emerged as a viable solution for meeting client requirements in getting an early return on investment, a high quality building, and an economically feasible construction. Precast concrete construction offers several green building benefits such as reducing construction wastes, minimizing site disturbances, and increasing flexibility. Although modular construction has been on the rise in Lebanon, many obstacles stand in the way of reaping more value for customers including technical, logistical, and organizational issues. This research aims at assessing the obstacles for efficient industrialized construction and exploring opportunities for improvement. The study reports results from industry-wide interviews covering all modular precast production companies, the major architects and design professionals, and class-A contracting companies. Findings of the study highlight that technical, logistical, and organizational/ cultural factors form the main obstacles, whereas cost, time, sustainability, and flexibility are the areas of opportunity for implementing efficient industrialized construction and increasing the uptake of precast concrete construction.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 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".