Feeling Appreciated Buffers Against the Negative Effects of Unequal Division of Household Labor on Relationship Satisfaction
Bibliographic record
Abstract
Decades of research from across the globe highlight unequal and unfair division of household labor as a key factor that leads to relationship distress and demise. But does it have to? Testing a priori predictions across three samples of individuals cohabiting with a romantic partner during the COVID-19 pandemic ( N = 2,193, including 476 couples), we found an important exception to this rule. People who reported doing more of the household labor and who perceived the division as more unfair were less satisfied across the early weeks and ensuing months of the pandemic, but these negative effects disappeared when people felt appreciated by their partners. Feeling appreciated also appeared to buffer against the negative effects of doing less, suggesting that feeling appreciated may offset the relational costs of unequal division of labor, regardless of who contributes more. These findings generalized across gender, employment status, age, socioeconomic status, and relationship length.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".