Feasibility and Implications of the Modular Construction Approach for Rapid Post-Disaster Recovery
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
The adverse social and financial impacts of catastrophic disasters are increasing as population centers grow. In recent years, destroying homes and infrastructures has resulted in a major loss of life and created countless refugees. For example, Hurricane Katrina in August 2005 damaged over 214,700 homes in New Orleans and forced over 800,000 citizens to live outside of their homes due to flooding. After disastrous events, the government agencies have to respond to post-disaster housing issues quickly and efficiently and provide sufficient resources for temporary housing for short-term disaster relief and reconstruction of destroyed and damaged housing for full rehabilitation. Modular construction is a promising solution for improving the process of post-disaster housing reconstruction because of its inherent characteristic of time-efficiency. This study aimed to evaluate the potentials and feasibility of the prefabricated/modular construction approach that can be adapted to facilitate the post-disaster recovery process. An extensive literature review has been carried out to identify the features of modular construction, which can add value to the post-disaster recovery process. To investigate the suitability and practicability of implementing modular construction for post-disaster reconstruction and to identify major barriers of its implementation, a survey has been conducted among Architecture, Engineering, and Construction (AEC) experts who have experience in prefabrication/modularization, and/or involved in post-disaster reconstruction projects. The results of the study indicate that prefabricated/modular construction is a promising approach to improve time-efficiency of post-disaster reconstruction and tackle challenges of current practices by its unique benefits such as reduced demand for on-site labor (overcome local labor pool constraints impacted by the disaster) and resources (overcome the shortage of equipment and materials), shorter schedule (due to concurrent & non-seasonal), reduced site congestion, and improved labor productivity (due to assembly line-like and controlled environment).
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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 | 0.000 | 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 it