Constructing the Boundaries of Retirement for Baby-Boomer Women: Like Turning Off the Tap, or Is It?
Bibliographic record
Abstract
We are at a unique point in history when an unprecedented number of women are beginning to retire. Earlier work has suggested that women have few identity concerns in retirement because they had less attachment to the labor force. In contrast, women of the baby-boomer generation are the first cohorts to have participated in significant numbers in the paid work force since the institutionalization of retirement. Using in-depth, semi-structured interviews, this article explores baby-boomer women’s process of leaving the paid work force and queries what retirement means to them. It focuses on the eroding boundary between work and retirement and issues of personal and social identity for the research participants. When women retire, they navigate a number of key boundaries between full-time, paid and other work and between their own transitions and the transitions of others in their lives. The women’s social identity reflects their experience of the intersection of retirement, aging, and gender. The themes that permeate the interviews include the loss of a primary identity without having a new positive identity to claim, being retired as a conversation stopper, and experiencing the invisibility that often comes with aging. Developing a unique identity and finding new meaning as a retiree is a challenging process for baby-boomer women as they negotiate “lingering identities” to avoid crossing the identity boundary from professional to retired. The article uses the words of the research participants to explore how they construct boundaries between work and retirement, the extent of their permeability, and the impact of women’s relationships and identity on those boundaries.
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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 | 0.011 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.021 | 0.028 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".