Mentoring relationships among managerial and professional women in Turkey
Bibliographic record
Abstract
Purpose – Although qualified women are still underrepresented at ranks of senior management in all countries, considerable progress has been made in identifying work experiences associated with career success and advancement. The studies of mentor relationships in North America have shown that women receiving more functions from their mentors reported benefits such as greater job and career satisfaction, and female mentors provided more psychosocial functions than did male mentors. The present study examined antecedents and consequences of mentor relationships in a sample of managerial and professional women working for a large organization in Turkey. The paper aims to discuss these issues. Design/methodology/approach – Data were collected from 192 women managers and professionals using anonymously completed questionnaires. Findings – The following results were obtained: having a mentor relationship had little impact on work outcomes, female and male mentors generally provided the same mentor functions, and mentor functions had little impact on work outcomes. Practical implications – Highlights the potential role of both organizational and societal values in mentoring programs. Originality/value – These findings are at odds with previously reported results obtained in Anglo-Saxon countries. Possible explanations for the failure to find previously reported benefits of mentoring are offered.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".