Caring in a Demanding Job: Examining Culture and Employee Well-Being Through a Gendered Perspective
Bibliographic record
Abstract
Employee well-being remains matter of significant concern for both workers and organizations. Despite progress, women and caregivers still face major challenges in organizations and environments characterized as greedy institutions and ‘ideal worker’ promoters. Our research further explores this environment using a contextual effects perspective with a large (n= 1,615) sample of employees across diverse jobs within a single organization to investigate the relationship between work and family demands, work-family conflict, and perceived stress in a male dominated, greedy organization. Specifically, this research has four key objectives. First, it aims to determine how role demands affect employee stress. Second, it assesses the impact of role interference on employee stress. Third, it examines the extent to which perceptions of the organizational culture (i.e., one that espouses the ideal worker image) affect the relationship between role overload and role interference, as well as the relationship between role interference and employee stress. Lastly, it explores gender differences in these relationships and assesses the significance of caregiving responsibilities on them. Our research findings will provide relevant insights into the relationships between organizational culture, gender, caregiving responsibilities, and employee stress in demanding work environments. Additionally, they will offer executives and HR professionals in such organizational contexts guidelines for implementing more inclusive and supportive cultures that benefit minority groups and caregivers.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".