A Conversation Worth Having: The Spillover Effects of Reproductive Health Hardships in the Workplace
Bibliographic record
Abstract
Although work-family researchers have made meaningful progress in understanding how parental and pregnancy experiences affect work, little has been done to understand the affects that reproductive health issues, including infertility, IVF, and miscarriage, have on employees at work. This symposium brings together four insightful empirical studies that examine the complex interplay between employees’ reproductive challenges and their professional lives. In doing so, this symposium begins an important and much-needed dialogue on the challenges that these hardships present to employees and the ways that they spillover into the work domain. By highlighting the need for innovative organizational policies and practices that are more inclusive of and supportive towards employees confronted with these challenges, this symposium strongly aligns itself with the Academy of Management’s 2024 conference theme of “Innovating for the Future: Policy, Purpose, and Organizations. Feeling Torn and Stuck: A Qualitative Investigation of Infertility Experiences Among Women and Men Author: Janet Boekhorst; U. of Waterloo Author: Laura McAndrews Little; U. of Georgia Author: Justin Peyton Woodall; U. of Georgia The Labors We Can't See: The Impact of Infertility on Women's Careers Author: Serena Sohrab; Bayes Business School Author: Nada Basir; U. of Waterloo Author: Jamie Jocelyn Ladge; Boston College From Grief to Hope and Back Again: The Emotional Complexities of Infertility Journeys at Work Author: Allison S. Gabriel; Purdue U., West Lafayette Author: Kristen Michelle Shockley; Auburn U. Author: Aqsa Dutli; Purdue U., West Lafayette Author: Hope Dodd; U. of Georgia Author: Beth Buchanan; - Understanding Working Women's Miscarriage Experiences Author: Nitya Chawla; U. of Minnesota, Twin Cities Author: Yu Tse Heng; U. of Virginia - McIntire School of Commerce Author: Beth Schinoff; U. of Delaware Author: Kristen Price Jones; U. of Memphis Author: Abbie Griffith Oliver; U. of Virginia
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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 | 0.018 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.033 | 0.027 |
| Scholarly communication | 0.012 | 0.014 |
| Open science | 0.002 | 0.017 |
| Research integrity | 0.005 | 0.013 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".