Organizational abortion support benefits in the post-Roe world: employee and employer perspectives
Bibliographic record
Abstract
Purpose The authors discuss the implications of the recent United States Supreme Court decision in Dobbs v. Jackson and its impact on employees and employers. Although several employers issued public statements regarding the provision of abortion-related benefits, the authors highlight some of the obstacles to their implementation. Design/methodology/approach With a focus on employee wellbeing, the authors discuss the obstacles in implementing abortion care benefits. Findings While it is encouraging to see many organizations make public statements in support of abortion rights, the authors temper their enthusiam with questions about practicality. Research limitations/implications Based on the research on hidden stigmas and the job demands-resources model, the authors argue that employees who need to use abortion-related benefits may be unlikely to seek them. Practical implications The authors highlight some unanswered questions relating to the requesting and granting of abortion healthcare benefits. Social implications The Dobbs decision takes away rights. While the authors applaud organizations’ efforts to restore them, facilitating access to an abortion in other states is quite complicated. Originality/value Although abortions are very common, very little organizational research has addressed the topic. In light of the Dobbs v. Jackson decision, the paper raises some timely questions about employer-sponsored abortion healthcare.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".