Parenting in a Pandemic: Work–Family Arrangements, <scp>Well‐Being</scp>, and Intimate Relationships Among Adoptive Parents
Bibliographic record
Abstract
The COVID‐19 pandemic presents unforeseen challenges to families. This mixed‐methods study aimed to address how 89 adoptive parents (lesbian, gay, heterosexual) with school‐age children are navigating a major public health crisis with social, economic, and mental health consequences. Specifically of interest were adoptive parents' worries and concerns; work–family arrangements; and mental, physical, and relational health, in the context of the pandemic and associated quarantine. Findings revealed that 70% of participants had changed work situations, with most newly working from home just as their children initiated remote homeschooling. The division of labor was rarely a source of stress, although the parent who was more involved in homeschooling sometimes experienced resentment. Concerns related to the pandemic included worries about health and children's emotional well‐being and global concerns such as the national economy. Almost half reported declines in mental health (e.g., due to the stress of working and homeschooling), with lesbians being significantly more likely than others to report declines. Declines in physical health were rarer (less than 20%), with more than a quarter reporting improvements (e.g., due to increased exercise). Few reported declines in relationship quality, although almost a quarter reported declines in intimacy. Findings have implications for family and health professionals.
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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 | 0.002 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".