Are Gender Roles Related to Purpose in Life and Well-Being in Younger and Older Females?
Bibliographic record
Abstract
Research shows that holding an egalitarian attitude towards gender roles has been associated with increased well-being, but inability to engage in life goals that reflect these attitudes may lead to feelings of restriction.The current paper looks at how gender roles are associated with purpose in life and well-being through both a quantitative assessment of a female university sample and a coded interview with retired women.The university sample showed no relationship between gender role attitudes and purpose in life, but a significant connection between traditional attitudes and greater depressive symptoms.It was found that older women mentioned gender roles when discussing purpose, and a greater proportion of egalitarian gender roles was associated with higher purpose in life.Based on these results, opportunities for future research and importance of implementing gender roles within a counselling setting are discussed.Parent, David Collict, Ella Chochla, and Sarah Royer who helped transcribe the verbal interviews, Shelby Levine and Casey Kapitany who helped conduct the interviews, and Emily Davison who helped both transcribe and separately code these interviews with me.Special thanks to Nathan Lewis,
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 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".