Re-thinking global and public health projects during the COVID-19 pandemic context: Considerations and recommendations for early- and not-so-early-career researchers
Bibliographic record
Abstract
This commentary aims to provide a glimpse into some of the early and continuing impacts of the COVID-19 pandemic on our global and public health projects: research in low-resourced settings; research with vulnerable populations, such as asylum seekers, Indigenous communities, children, and mental health service users; and research with healthcare professionals, frontline workers, and health planners. In the early context of restrictions caused by COVID-19, this commentary highlights our research setbacks and challenges, and the ways in which we are adapting research methodologies, while considering ethical implications related to the pandemic and their impacts on conducting global and public health research. As we learn to become increasingly aware of some of our limitations in the face of the pandemic, some positives are also worth highlighting: we are mobilizing our training and research skills to participate in COVID-19 projects and to disseminate knowledge on COVID-19, including through papers such as this one. However, we do acknowledge that these opportunities have not been equitable. Each thematic section of this commentary concludes with key recommendations related to research in the early and continuing context of the COVID-19 pandemic that we believe to be applicable to early- and not-so-early-career researchers working in the global and public health fields.
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.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.001 | 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".