Correlates and Consequences of Misjudging Romantic Partners’ Work and Family Priorities
Bibliographic record
Abstract
Women still complete the preponderance of unpaid domestic labour, even when employed full-time. Conversely, despite lessening pressures on men to provide financially, men have not seen a commensurate uptick in domestic work. I propose that inaccurate interpersonal perceptions between men and women are a key mechanism driving these uneven changes to gender roles. I mega-analytically analyzed the work and family goals of 435 mixed-gender romantic couples in Canada, then calculated women’s and men’s inaccuracies when appraising their partners’ goals. On average, women wanted more egalitarian romantic relationships than men, a gap compounded by men underestimating their partners' desire for egalitarianism. Further, men (especially those who saw their partners as highly feminine) simultaneously overestimated their partners' orientation toward family goals (over career goals) and their career intensity. Women also misperceived their partners, but here expectations were fairly low: Women underestimated their partners' family goals and career intensity. Turning to long-term outcomes, modest evidence emerged that people with inaccurate partners experienced lower relationship well-being within the next two years. Perceiving partners as being generally poor at perspective-taking (distinct from their actual inaccuracy) was the most powerful predictor of both relationship dissolution and worsened relationship well-being. These findings clarify common misperceptions between romantic partners and illuminate the consequences of having—or perceiving you have—a partner who does not understand your work and family goals.
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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 | 0.004 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 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".