Assessing Mentoring Culture: Faculty and Staff Perceptions, Gaps, and Strengths
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The purpose of this non-experimental, cross-sectional, descriptive research was to survey faculty and staff perceptions of mentorship in a postsecondary institution in order to determine gaps and strengths in the current mentorship environment. The anecdotal activities we present reflect our educational practice environment through the work of our Mentorship Team. Data were collected utilizing Zachary’s Mentor Culture Audit tool. The culture building block measured 4.65 on a 7-point Likert scale, suggesting the presence of a weak mentorship culture. However, the infrastructure building block measured only 3.41, showing that organizational resources and supports are below average. We also present eight hallmark category results to further identify strengths and gaps. This is the first assessment of our mentoring culture at an organizational level. Other postsecondary institutions may benefit from formally assessing the gaps in and strengths of their mentorship culture to assist them with acquiring adequate resources to further develop and sustain their mentoring activities.
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.
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) | 0.000 | 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 it