LESSONS LEARNED FROM TWO DECADES OF SEISMIC RETROFIT PROGRAM IMPLEMENTATION IN BC, CANADA
Bibliographic record
Abstract
In 2004, the Ministry of Education (EDUC) engaged Engineers and Geoscientists British Columbia (EGBC), with support from the University of British Columbia (UBC), to assist with the implementation of a seismic upgrade program for British Columbia (BC) schools. This program included the development of tools and guidelines for the performance-based seismic assessment and retrofit of BC school buildings. Five versions of the Seismic Retrofit Guidelines (SRG) have been released to date: interim Bridging Guidelines (2006), SRG-1 (May 2011), SRG-2 (November 2013), SRG-3 (June 2017), and SRG2020 (September 2023). Currently, the EDUC oversees approximately 1600 provincial public schools, out of which approximately 500 have been classified as high-risk using SRG and are included in the seismic mitigation program. Half of these high-risk schools have achieved significant progress, either through successful completion, being currently under construction, or having a business case developed using SRG cost-effective retrofit schemes. This paper provides insights into the lessons learned during the development and implementation of the SRG performance-based methodology over the past two decades. It focuses the challenges of aligning the SRG with changes in seismic hazard models from the National Building Code Canada (NBCC). These changes include significant increases in ground motion hazard, particularly from long-duration Cascadia subduction interface events, leading to more intense shaking in Southwestern BC than previously anticipated. NBCC 2015 introduced a seismic hazard shift, leading to a reassessment of numerous schools using SRG3. Consequently, previously low-risk school blocks were added to the moderate- and high-risk list. NBCC 2020 introduced further revisions in seismic demands along the West Coast of BC, incorporating new ground motion models that had a substantial impact on areas with soft soils. The challenge of adopting these new hazard demands and methodologies to mitigate the seismic risk are discussed. Additionally, this paper summarizes the current state of the province-wide retrofit program and presents an example project that employs the SRG performance-based methodology to assess and retrofit school blocks. This project example showcases a retrofit journey spans over a decade, encompassing the crucial phases of assessment, design, and construction. It effectively incorporates and adapts to the evolving changes and updates within SRG.
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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 | 0.001 |
| 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".