Bibliographic record
Abstract
A looming attrition rate, a steady increase in the number of women in administration, and a lack of Canadian research all provided the rationale for this study. The problem in this study was to investigate the needs and challenges of new female administrators and to examine the role that mentors play in addressing these issues. This study also explored the perceived benefits of having a mentor. This study examined the inductive year of 33 female administrators from 3 Ontario school boards. It was a qualitative and quantitative design, using questionnaire and interview data. It was found that the majority felt that they struggled with biases and expectations that were gender specific. The challenges that were perceived to be most prevalent were categorized into 4 thematic areas: Maintaining Balance, Feeling Pressured, The Perceptions of Others, and Being Challenged by Others. Regarding the benefits of mentoring, the participants perceived mentoring to be most beneficial in terms of professional growth, followed by learning how to run a school, and then career advancement. The significance of this study was threefold: it had theoretical implications as well as implications for practice and future research. Suggestions included: facilitating longitudinal relationships, having the board become more actively involved in facilitating the relationship, and implementing an internship program. This study attempted to extend the current literature by theorizing that a mentorship is cyclical in nature. Future research could include program design and implementation, as well as providing consistent and accessible mentoring opportunities for all.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.030 | 0.008 |
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 source (direct Gemma or distilled Codex), 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".