Through Their Own Eyes: The Implications of COVID-19 for PhD Students
Bibliographic record
Abstract
Abstract COVID-19 is expected to radically alter higher education in the United States and to further limit the availability of tenure-track academic positions. How has the pandemic and its associated fallout affected doctoral students’ career aspirations and priorities? We investigate this question by comparing responses to a PhD career survey prior to and following significant developments in the pandemic. We find little evidence that the pandemic caused substantial shifts in PhD students’ aspirations and priorities. However, some differences emerge when considering later dates in our survey period, particularly among more senior students who express a greater interest in some non-academic careers and job characteristics. Contrary to expectation, we also find evidence that the pandemic improved some students’ perceptions of their academic departments. In our conclusion, we speculate whether steps taken by the comparatively well-resourced institution that we study helped to mitigate some of the more negative consequences of the pandemic.
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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 | 0.032 | 0.104 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.010 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.027 | 0.003 |
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".