Mentoring for Wellbeing in Higher Education
Bibliographic record
Abstract
This volume of the Perspectives on Mentoring Series focuses on the connections between mentoring and wellbeing in organizational cultures within higher education institutions. Increasing competition, societal pressures, and the changing nature of the cultures within the United States and Canada, the countries represented in this volume’s chapters, have created complex personal, social, and institutional problems that have negatively affected the wellbeing of individuals, and subsequently institutional success. As a result, higher education institutions need to become more actively engaged in creating initiatives, programs, activities, and organizational cultures that support the wellbeing of students, faculty, staff, and administrators. The notion of wellbeing, in general, includes both hedonic aspects of feeling good (positive emotions) and eudemonic (conducive to happiness) aspects of living well that entail experiences of positive relationships, meaningfulness in life and work, senses of mastery and personal growth, autonomy, and achievement. This book proposes that one of the key avenues for fostering wellbeing in institutions of higher education is through mentoring. However, the research on the positive impact that mentoring can have on the mental health and wellbeing of both the mentor and mentee in higher education is fairly limited. This edited volume expands and adds to the existing literature on mentoring in higher education, by offering a collection of works that examine the connection between mentorship and wellbeing in relation to potential students, undergraduate and graduate students, and faculty and leaders. Of particular interest for this edited volume is how mentoring can promote mental health, build resilience, and develop capacity to maintain and sustain emotional, psychological, and social wellbeing for all in the higher education settings. Chapters in this volume describe mentoring of emerging adults and students through positive relationships, illustrate the impact of peer mentoring, mindfulness, resilience-growing, capacity building, and leadership development initiatives on undergraduate students, detail positive and effective mentoring strategies to growing wellbeing and thriving of graduate students, and discuss studies and models for nurturing and promoting wellbeing among faculty and leaders in higher education institutions. Through their chapters, authors present stories and perspectives regarding higher education endeavors or research studies to foster a greater understanding of how mentoring can enhance the wellbeing of varied constituencies in higher education. In addition, there are common themes about fostering wellbeing in higher education institutions that permeate these hapters, provide ideas for reflection, and create a body of knowledge and new avenues for future research and study.
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 | 0.000 | 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) | 0.004 | 0.001 |
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; both teacher heads agree on what is shown here.
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".