Analyses of Mentoring Expectations, Activities, and Support in Canadian Academic Libraries
Bibliographic record
Abstract
Mentoring expectations, activities, and support in Canadian college and university libraries were investigated by surveying 332 recent MLIS graduates, practicing academic librarians, and library administrators. Findings indicate that the presence of a mentoring program will help attract new librarians, retain them, and aid in restructuring efforts that are currently facing many academic libraries. Preferred mentoring activities include those belonging to psychosocial support, career guidance, and role modeling themes. Other results find that librarians who were mentored as new librarians, have more than 10 years of experience, and work in large academic institutions are significantly more likely to mentor others. Although currently not well-supported by academic administrators, this research shows that mentoring programs could be sustainable. Mentoring improves the professional experience for librarians who are more satisfied and engaged with their careers, which in turn benefits the organization with less turnover. Practical information from this research will guide academic library practitioners in current mentoring relationships, and library leaders can extrapolate results to support planning and implementation of mentoring programs. Implications for LIS education are also discussed.
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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 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.008 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".