Transforming Disruption Into Innovation: A Partnership Between the COVID-19 Medical Student Response Team and the University of British Columbia
Bibliographic record
Abstract
The COVID-19 pandemic caused substantial disruptions in medical education. The University of British Columbia (UBC) MD Undergraduate Program (MDUP) is the sixth-largest medical school in North America. MDUP students and faculty developed a joint response to these disruptions to address the curriculum and public health challenges that the pandemic posed. After clinical activities were suspended in March 2020, third- and fourth-year MDUP students formed a COVID-19 Medical Student Response Team (MSRT) to support frontline physicians, public health agencies, and community members affected by the pandemic. A nimble organizational structure was developed across 4 UBC campuses to ensure a rapid response to meet physician and community needs. Support from the faculty ensured the activities were safe for the public, patients, and students and facilitated the provision of curricular credit for volunteer activities meeting academic criteria. As of June 19, 2020, more than 700 medical students had signed up to participate in 68 projects. The majority of students participated in projects supporting the health care system, including performing contact tracing, staffing public COVID-19 call centers, distributing personal protective equipment, and creating educational multimedia products. Many initiatives have been integrated into the MDUP curriculum as scholarly activities or paraclinical electives for which academic credit is awarded. This was made possible by the inherent flexibility of the MDUP curriculum and a strong existing partnership between students and faculty. Through this process, medical students were able to develop fundamental leadership, advocacy, communication, and collaboration skills, essential competencies for graduating physicians. In developing a transparent, accountable, and inclusive organization, students were able to effectively meet community needs during a crisis and create a sustainable and democratic structure capable of responding to future emergencies. Open dialogue between the MSRT and the faculty allowed for collaborative problem solving and the opportunity to transform disruption into academic innovation.
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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 | 0.022 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.035 | 0.015 |
| Scholarly communication | 0.021 | 0.004 |
| Open science | 0.003 | 0.020 |
| Research integrity | 0.007 | 0.014 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".