Bibliographic record
Abstract
Purpose This case study aims to report on the effectiveness of a matrix mentoring pilot project in a healthcare setting and its ability to build managerial competencies and enhance levels of employee engagement. Design/methodology/approach The study used a mixed‐method design with pre and post pilot evaluation phases. Focus groups were held with both mentee and mentor groups. Mentees also completed questionnaires that assessed their levels of managerial competency and engagement. Findings Mentees who engaged in a matrix mentoring pilot reported increased levels of managerial and leadership competencies, and employee engagement. Additionally, mentees realized greater exposure to managerial roles and responsibilities and experienced personal development and growth as a result of individual project assignments. Research limitations/implications The small sample size is the main limitation of this project. However, it was a pilot within a case study organization and one of the objectives was to learn from the experience. Practical implications Mentors and mentees reported positive feedback. Mentors were able to assess the capacity and interest of future potential leaders and mentees gained exposure to managerial competencies. Originality/value The originality of this research is found in the application of a matrix mentoring approach. Typically, mentoring programs match one mentor with one mentee. A team of mentors worked with each of the mentees and engaged in exposing the participants to a range of competencies. The literature suggests that managerial competencies in a complex setting, like healthcare, need to be diverse. This research presents one possibility for building such a range of abilities.
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 | 0.002 | 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) | 0.001 | 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".