Librarians: The next generation. Mentorship at the University of Toronto
Bibliographic record
Abstract
Abstract Librarians: The next generation. Mentorship at the University of Toronto LibrariesMentoring is to librarianship what chocolate syrup is to ice cream sundaes: a delicious anddefining feature. The profession prides itself on initiating its newest members into the fold and avariety of approaches to mentorship for up and coming librarians are underway at the Universityof Toronto. For example, practicums for library and information science (LIS) students, and anew internship program at the University of Toronto Libraries for top incoming LIS students.These programs are facilitated by the fact that the University of Toronto is home to a topInformation school that has been dedicated to training new librarians since 1928. The authorswill present their experience working with student librarians at the engineering library, which onseveral occasions has led to graduate student workers who return for full-time professionalpositions – a testament to the mutual benefits of the relationship.The authors will also discuss the ongoing mentoring of the newest engineering librarians on theirteam. These efforts include invitations to meetings with engineering faculty to facilitatenetworking, involvement in a variety of decision making processes, and careful training for ahost of new responsibilities. The team’s more experienced librarians impart their expertise andact as coach and counsellor, providing critique and encouragement as necessary. Priorities alsoinclude acculturation and socialization to the library environment. More generally, the Universityof Toronto intrinsically mentors its librarians by requiring professional development activities asa condition for achieving permanent (tenured) status. The mentoring relationship has provenbeneficial for the mentors as well. Knowledge transfer and reflecting on career pathways canprovide perspective and motivation for experienced librarians. Additionally, the authors willpresent on areas for improvement and recommendations for future mentoring initiatives. Thediscussion will include a review of the research related to mentoring new employees, includingfindings that show a direct correlation between active mentoring practices and employeeretention rates.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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".