Career priority patterns among managerial and professional women in Turkey
Bibliographic record
Abstract
Purpose This research aims to examine potential antecedents and consequences of different career priority patterns among managerial and professional women working in a large Turkish bank. Two career priority patterns advanced by Schwartz were considered: career‐primary and career‐family. Previous research conducted in other countries has compared these career priority patterns. Design/methodology/approach Data were collected from 286 managerial and professional women using anonymously completed questionnaires, a 72 percent response rate. Findings Career‐primary and career‐family women were similar on personal demographic and work situation characteristics. However, the two groups were significantly different on a variety of other measures. Career‐primary women were more satisfied with their jobs and careers, had more optimistic career prospects, were more work engaged, exhibited higher levels of workaholism and reported higher levels of psychological well‐being. These findings were somewhat different from those obtained in previous research suggesting possible country and culture differences. Research limitations/implications All data were collected using questionnaires at one point in time making it difficult to draw conclusions on causality. It is also not clear the extent to which these findings would generalize to women in other occupations. Practical implications The findings raise potential career development issues and their role in the satisfaction and well‐being of managerial women, these having possible career counseling implications. Originality/value This study replicates previous work and extends this to another county. Future research should be devoted to greater understanding of country and culture effects on the findings.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".