Impact of COVID-19 pandemic on research and careers of early career researchers: a DOHaD perspective
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
The COVID-19 pandemic has exposed several inequalities worldwide, including the populations' access to healthcare systems and economic differences that impact the access to vaccination, medical resources, and health care services. Scientific research activities were not an exception, such that scientific research was profoundly impacted globally. Research trainees and early career researchers (ECRs) are the life force of scientific discovery around the world, and their work and progress in research was dramatically affected by the COVID-19 pandemic. ECRs are a particularly vulnerable group as they are in a formative stage of their scientific careers, any disruptions during which is going to likely impact their lifelong career trajectory. To understand how COVID-19 impacted lives, career development plans, and research of Developmental Origins of Health and Disease (DOHaD) ECRs, the International DOHaD ECR committee formed a special interest group comprising of ECR representatives of International DOHaD affiliated Societies/Chapters from around the world (Australia and New Zealand, Canada, French Speaking DOHaD, Japan, Latin America, Pakistan and USA). The anecdotal evidence summarized in this brief report, provide an overview of the findings of this special interest group, specifically on the impact of the evolving COVID-19 pandemic on daily research activities and its effects on career development plans of ECRs. We also discuss how our learnings from these shared experiences can strengthen collaborative work for the current and future generation of scientists.
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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 | 0.014 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it