The Family-Supportive Workplace: Understanding Supervisor and Organizational Support for Family
Bibliographic record
Abstract
Formal work-life policies that provide employees with increased flexibility in the scheduling and the location of their work have been associated with a variety of favorable work outcomes such as high levels of productivity and job satisfaction and low levels of work-family conflict, absenteeism, turnover intent, and role stress. Nevertheless, informal work-family support provided by supervisors and the broader organizational environment has an even stronger effect on these outcomes than do formal policies. This symposium brings together four papers that address important gaps in the literature on informal work-family support by examining the antecedents of family-supportive supervision, the role of family-supportive supervision in shaping employees’ reactions to workplace aggression, and the effect of family-supportive organizational perceptions on employees’ affective organizational commitment as mediated by partners’ attitudes toward employees’ job conditions. Together, the four papers increase our understanding of the organizational and individual characteristics that give rise to family-supportive supervision, the degree to which family-supportive supervision can buffer employees from the effects of aggression from coworkers, and how family-supportive organizations can influence employees’ partners as well as the employees themselves.Organizational, Supervisor, and Employee Antecedents of Family-Supportive Supervision Presenter: Katrina A. Graham; Drexel U.Presenter: Jeffrey H. Greenhaus; Drexel U.Presenter: Jaclyn Shor; Drexel U.A Multi-level Model of Antecedents of Work-Family Support, Conflict and EffectivenessPresenter: Ellen Ernst Kossek; Michigan State U.Presenter: Leslie B. Hammer; Portland State U.Presenter: Todd Bodner; Portland State U.Presenter: Jesse S. Michel; Florida International U.Presenter: Ryan Petty; Roosevelt U.Presenter: Nanette L. Yragui; Sharp ProgramHorizontal Aggression, Family-Supportive Supervisory Behavior, and Work-Family ConflictPresenter: Sarah Van Dyck; Portland State U.Presenter: Leslie B. Hammer; Portland State U.Family-Supportive Organization Perceptions, Partner Attitudes, and Organizational CommitmentPresenter: Julie Holliday Wayne; Wake Forest U.Presenter: Wendy J. Casper; U. of Texas, ArlingtonPresenter: Tammy D. Allen; U. of South FloridaPresenter: Russell A. Matthews; Louisiana State U.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".