Women’s perspectives on career successes and barriers: A qualitative meta-synthesis
Bibliographic record
Abstract
Despite scholarly debate on the topic of success, how women define career success remains unclear. For many decades, research on the concept of success has largely used quantitative methods to assess the external aspects of success in a male-dominated culture. Using a total of 18 articles from 1999 to 2020, this qualitative meta-synthesis aims to gain detailed insights into women’s definitions of career success and to capture their perspectives on the barriers they face. A systematic search was conducted across four databases: Sociological Abstracts, SocINDEX, SCOPUS, and Google Scholar. This study is novel in that it is the first synthesized research that qualitatively studies the concept of career success. From this review, three distinct themes regarding women’s definition of career success emerged: (1) having support, (2) having accomplishments, and (3) feeling belonging. This article also establishes three themes regarding the obstacles to women’s career path toward success: (1) work–family/work–life imbalance, (2) gender bias/gender discrimination, and (3) the lack of mentors and role models. In contrast to previous research, the findings of this qualitative meta-synthesis indicate that while women define career success individually, they acknowledge that the professional objective aspects of success are important or even central to them in their life. The limitations of the study are noted, and the implications and future research directions are discussed.
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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 | 0.085 | 0.150 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.019 | 0.018 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".