Bibliographic record
Abstract
Once considered the preserve of the wealthy, nanny care has grown in response to changes in the labour market, including the rising number of mothers with young children, and increases in non-standard work patterns. This book examines the place of in-home childcare, commonly referred to as care by nannies, in Australia, the United Kingdom and Canada since the 1970s. In contrast to childminding or family day care provided in the home of the carer, in-home care takes place in the child’s home. The research extends beyond the early childhood education and care domain to consider how migration policy facilitates the provision of childcare in the private home. New empirical research is presented about in-home childcare in Australia, the United Kingdom and Canada, three countries where governments are pursuing new ways to support the recruitment of in-home childcare workers through funding, regulation and migration. The compelling policy story that emerges illustrates the implications of different mechanisms for facilitating in-home childcare - for families and for care workers. It proposes that these differences are shaped by both structural and normative understandings about appropriate forms of care that cut across gender, class/socioeconomic status and race/migration. Overall, it argues that greater attention needs to be given to the way childcare work in the private home is situated across ECEC and migration policy.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".