Opportunities for Community Wellbeing in Times of Emergency Response at UBC
Bibliographic record
Abstract
The COVID-19 pandemic triggered a wave of mass shutdowns across the globe in early 2020, and UBC’s Vancouver campus was no exception. As classes moved online and social distancing regulations were implemented, concerns were raised about community wellbeing within the student population. This project aimed to investigate existing gaps in UBC’s current response to the pandemic, as well as provide recommendations to improve future emergency response strategies. This project involved the conduction of in-depth interviews with both current students and stakeholders within the UBC community, as well as an online student survey and a literature review. The main research question investigated was ‘What are the best practices in community wellbeing that can be proposed for future emergency preparation and response strategies at UBC, based on the evaluation of the current COVID-19 response?’ The most promising initiatives adopted in other universities and communities were identified as being the creation of student volunteer emergency response teams and the adoption of culturally sensitive pandemic planning methods. Both strategies demonstrate great potential to be implemented at UBC. The most vulnerable student groups during the COVID-19 pandemic were identified, with international students recognized as being particularly vulnerable, as well as students with dependents, immunocompromised students and students of lower socio-economic status. Finally, gaps in UBC’s current resources were identified and examined, with lack of communication and advertisement emerging as a large factor. Based on these findings, several recommendations were made, including the implementation of a student volunteer emergency response team at UBC, the creation of a new and accessible online mental health resource and the establishment of a centralized location where students could access information regarding all resources available to them. Disclaimer: “UBC SEEDS provides students with the opportunity to share the findings of their studies, as well as their opinions, conclusions and recommendations with the UBC community. The reader should bear in mind that this is a student project/report and is not an official document of UBC. Furthermore readers should bear in mind that these reports may not reflect the current status of activities at UBC. We urge you to contact the research persons mentioned in a report or the SEEDS Coordinator about the current status of the subject matter of a project/report.”
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.024 | 0.007 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.002 | 0.020 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.018 | 0.002 |
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".