When the labs closed: graduate students’ and postdoctoral fellows’ experiences of disrupted research during the COVID-19 pandemic
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Government imposed lockdown measures in response to the COVID-19 pandemic resulted in widespread laboratory closures. This study aimed to examine the impact of this disruption on graduate students and postdoctoral fellows completing laboratory-based research in Canada. We used an anonymous online survey and semi-structured interviews to document the experiences of graduate students and postdoctoral fellows during laboratory closures and following the transition to working from home. We employed a mixed-method approach using survey and interview data to identify shared experiences, concerns, and supports. The emotions reported by respondents at different points during laboratory closures align with the Kübler-Ross model of grief following change. Respondents describe closure processes as chaotic and confusing, primarily resulting from inconsistent communication. Respondents reported increased indications of distress while working from home. Concerns about how COVID-19 might impact trainees were identified, including decreasing competitiveness of applicants while limiting future employment opportunities. Finally, we outline five types of supports that can be implemented by supervisors and administrators to support graduate students and postdoctoral fellows to return to the laboratory. Overall, we document shared experiences of respondents during the COVID-19 laboratory shutdown and identify areas of improvement in the event widespread laboratory closures occur in the future.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it