Earthquake risk mitigation of hospital facilities: a case study of Vancouver General Hospital
Bibliographic record
Abstract
The purpose of this study is to critically examine whether hospitals located in high seismic risk areas such as Vancouver can respond as post-disaster facilities in the aftermath of a major earthquake. Earthquake experience in California during the 1971 San Fernando and the 1989 Loma Prieta earthquakes in particular demonstrate that hospitals may be vulnerable and rendered unable to fully respond to their communities needs. In the case of earthquakes, risk management methods are limited to two strategies: pre-event mitigation to reduce the effects of the earthquake on life safety and loss of property; and providing recovery services after the event. In the case of post-disaster hospitals, experience shows that mitigation strategies ensure the functionality of the facility. Therefore, mitigation strategies must not only include structural mitigation to protect the life safety of its occupants, they must also include strategies which ensure the functionality of both the building operations as well as that of therapeutic and diagnostic medical equipment in the aftermath of an earthquake. Vancouver General Hospital is used as a case study to critically examine seismic pre-event mitigation strategies which include: the structures; building operation and medical equipment which are dependent on the supply of potable water and power. Findings of this study indicate that the current supply of potable water is not reliable and that some of VGH's essential building operations and medical equipment will not be functional due to losses in water pressures and disruptions in service. This study recommends that VGH should consider mitigation strategies which make the hospital independent of outside sources of both water and power supply in order to meet its emergency role as a post-disaster facility following an earthquake. The functionality of VGH in the aftermath of a major earthquake will be seriously curtailed unless there is adequate storage of potable water on site to meet the emergency needs of this hospital.
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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 | 0.000 | 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 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".