Plans and Experiences of Postdoctoral Scholars in the Chemical Sciences
Bibliographic record
Abstract
Abstract This account examines experiences and plans of over 400 postdoctoral scholars in the chemical sciences using data gathered by the American Chemical Society (ACS) in 2019. The sample was evenly divided among U.S. citizens, permanent residents, and international scholars. The vast majority reported satisfaction with their experiences, good relationships with their mentors, and confidence in their professional knowledge and preparation. However, there was substantial variability in employment-related benefits and yearly incomes. Over a quarter indicated that their funding was not sufficient to meet the cost of living in their location. About a third indicated that working in industry or government was their first choice for a future career. Only slightly more than half indicated confidence in preparation for future careers, and a third reported experiencing some type of problem during their experience. Scholars who received less than the desired support from mentors and colleagues, whose funding was not adequate to meet the cost of living and/or who had encountered problems expressed significantly less satisfaction with their experience. There were no differences in reported satisfaction associated with gender identity, parent level of education, identification with a group historically under-represented in the field, marital or parental status, or domestic or international background. Policy implications are discussed, including standardization of salaries, recruitment, and employment arrangements; incorporating career and professional development into the postdoctoral experience; recognizing postdoctoral scholars as educators and leaders; and fostering a culture of respect and inclusion that recognizes postdoctoral scholars as valued members of the academic community.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".