Familydemic Cross Country and Gender Dataset on work and family outcomes during COVID-19 pandemic
Bibliographic record
Abstract
Here we present the Familydemic Cross Country and Gender Dataset (FCCGD), which offers cross country and gender comparative data on work and family outcomes among parents of dependent children, before and during the COVID-19 pandemic. It covers six countries from two continents representing diverse welfare regimes as well as distinct policy reactions to the pandemic outbreak. The FCCGD was created using the first wave of a web-based international survey (Familydemic) carried out between June and September 2021, on large samples of parents (aged 20-59) living with at least one child under 12 in Canada, Germany, Italy, Poland, Sweden, and the US. While individual datasets are not available due to country-level restriction policies, the presented database allows for cross-country comparison of a wide range of employment outcomes and work arrangements, the division of diverse tasks of unpaid labour (housework and childcare) in couples, experiences with childcare and school closures due to the pandemic and subjective assessments of changes to work-life balance, career prospects and the financial situation of families (234 variables).
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.005 |
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".