Exploring Mentorship in Higher Education: Introduction to the Fifth Volume of Papers on Postsecondary Learning and Teaching
Bibliographic record
Abstract
The fifth volume of Papers on Postsecondary Learning and Teaching (PPLT) is a collection of papers from the 2021 University of Calgary Conference focused on the theme of Mentorship in Higher Education.Since the 2020 conference was cancelled due to the COVID-19 pandemic, PPLT heartily welcomes back authors this year for its fifth volume.Although the pandemic has caused disruptions and transitions in postsecondary research, learning and teaching, it has revealed insights for both students and academics.The papers in the volume are organized to reflect the stages of the academic lifespan, from student to professor emeritus.Perspectives from multiple disciplines present the shared common theme that all forms of mentorship in higher education are beneficial to students, instructors, the institution, and graduates. Mentorship ModelsLorelli Nowell (2022), one of the conference keynote speakers, presents in her paper, "Beyond tradition: Innovative mentorship models for higher education", a comprehensive overview and description of the various models of mentorship, which includes peer, group, distance, and constellation models.Her introduction sets the stage for the rest of the papers in this volume as they explore various models from diverse perspectives and disciplines to further our understanding and practice of mentorship in higher education.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".