Research, Promotion and Tenure Guidelines for Academic Librarians
Bibliographic record
Abstract
Renewal, promotion, and tenure (RPT) are often the most stressful career milestones an academic librarian can face. These events can dictate the course of a librarian’s career. It would stand to reason that RPT guidelines would be thorough and exhaustive in order to better help librarians achieve these milestones. The purpose of this paper is to identify the requirements for academic librarians to receive RPT and determine how they align with standards of assessment for job performance. The authors reviewed libraries in Canada’s U15 Group of Research Institutions for any collective agreements or regulations documenting the RPT process. Eleven of the fifteen institutions had public facing documents, and each of these universities require successful job performance in professional practice, research, and service in order to achieve RPT. The authors apply the Management by Objective (MBO) practice to the findings to better understand how RPT guidelines can be improved to help librarians achieve these career milestones.
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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 | 0.113 | 0.249 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 0.007 |
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".