Empowering Postdoctoral Scholars: Insights From Library Focus Groups
Bibliographic record
Abstract
Objective – The goal of this study was to assess how postdoctoral scholars (postdocs) engage with the campus library and identify barriers to access. Postdocs occupy a unique position within the research community, bridging the gap between graduate studies and permanent academic positions. Despite their critical role, there has been little formal research to examine how postdocs interact with library resources and services, likely due in part to their relatively small numbers at academic and research institutions. Methods – Three focus group interviews were conducted at two research intensive institutions in the United States. The qualitative analysis employed an iterative coding process to explore several themes: self-proclaimed needs to succeed during postdoctoral training; perceptions of library offerings, including space, services, and collections; and barriers to success. Results – The thematic analysis revealed that postdocs value library resources and are seeking a range of services including financial services, mentorship, and scholarly writing support. There were only minor differences observed between the two institutions. The study identified lack of communication and time as the main barriers postdocs cited for not using the library. Based on participant feedback, we developed recommendations to enhance the postdoctoral experience with library resources and support their career development. Conclusion – This study contributes valuable insights into optimizing library services for postdocs and highlights opportunities for libraries to better align their offerings with the unique needs and challenges faced by this sector of the academic community. Our approach also serves as a model to assess and improve library offerings to other small communities.
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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 | 0.057 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.015 | 0.008 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.002 | 0.003 |
| 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".