Construction Capacity and New Housing Demand Caused by Tornados
Bibliographic record
Abstract
Recent research shows that construction of new houses takes the majority of the recovery time after a tornado. The rapid procurement of new houses depends largely on the existing construction capacity in the region affected. In this study, information about the construction industry in a tornado-prone region is extracted from U.S. economic Census data by using NAICS (North American Industry Classification System) categories. The present capacity of the construction industry is calculated by extracting (1) the inventories of materials and supplies, and (2) the value of new houses put in place in a targeted tornado-prone region, in this study, Oklahoma. A method is proposed to calculate the extra construction capacity in the targeted region using the information extracted from U.S. Census data. The extra construction capacity hence calculated is then compared to the anticipated need for new houses after a severe tornado, calculated by considering the historical records of damages caused by past tornados. The results of the study indicate that the existing construction capacity in the Oklahoma region is not enough to rapidly respond to the anticipated need for new houses after a tornado.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".