Child care participation among Indigenous children in Canada
Bibliographic record
Abstract
The release of a Canadian Indigenous Early Learning and Child Care Framework highlights the importance of recent, Indigenous-specific information to describe the landscape of child care among Indigenous children in Canada; however, there has been a gap in identity-specific, national data on child care for Indigenous children. The purpose of the current study was to address data gaps on participation in child care for First Nations children living off reserve, Métis, and Inuit children. Furthermore, two years of data are examined which provide information on child care use both prior to and during the first year of the COVID-19 pandemic. In 2019, First Nations children living off reserve (49%) and Inuit children (42E %)1 were significantly less likely to participate in child care compared with non-Indigenous children (60%), although Métis children (60%) were equally likely to participate in child care compared with non-Indigenous children. Only First Nations children living off reserve (40%) were significantly less likely than non-Indigenous children (53%) to participate in child care in 2020. In terms of the type of child care used, Inuit children were more likely to be in a daycare centre (70%) compared with non-Indigenous children (52%) in 2019, although Inuit children’s participation in a daycare centre dropped to 46E% in 2020. This is likely due to public health restrictions which closed many child care centres during the pandemic, as over one-third of child care in the territories is centre-based. The findings provide important information about patterns of child care use for Indigenous children both before and during the pandemic.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".