Academic Research Librarians with Subject Doctorates: Experiences and Perceptions 1965-2006
Bibliographic record
Abstract
The topic of academic/research librarians with subject doctorates remains largely unexplored. Based on survey data gathered from subject-doctorate holders (excluding those with doctorates in LIS) currently working in U.S. and Canadian academic/research libraries, this article extends the analysis published by the authors in the January 2008 issue of portal: Libraries and the Academy. While the first article featured quantitative analysis to highlight data and trends relating to these librarians over a 40-year period, focusing on their demographic profile, educational background, paths into librarianship, and range of positions, this article analyzes qualitative data to report their perceptions about their work environment and the advantages and challenges of academic librarianship as a career. Providing more information about this group of librarians and their experiences highlights the valuable skills they bring to the academic/research library environment. Moreover, it can help advanced-degree holders to determine whether a career in librarianship is right for them.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.000 | 0.020 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".