Values, policies and the well-being of young children in Canada, Norway and the United States
Bibliographic record
Abstract
Introduction This chapter explores connections that exist among values, policies and outcomes for young children in Canada, Norway and the United States. For example, values are likely to be directly associated with the wellbeing of children by influencing parenting styles and the expectations which parents have for their children. Values may help to shape social policies that affect the well-being of children; existing social policies may help to shape the values of the people who experience them. Social policies available to families with young children might be expected to have important associations with family poverty status as well as indicators of children’s well-being such as physical or emotional health or success at school; perceptions about problems/success of children will influence perceived social policy needs. To examine some of these connections, use is made in this chapter of three different collections of microdata from the early to mid-1990s: The World Values Survey (1990); the Luxembourg Income Study (LIS) (1994 and 1995); and three microdata surveys which provide information about child health and well-being (the Canadian National Longitudinal Survey of Children and Youth (1994/95); the Norwegian Health Survey (1994) and the US National Longitudinal Survey of Youth – Mother/Child Survey (1994). An obvious question to ask at this stage is why it makes sense to study Canada, Norway and the US? The US and Canada are obvious choices for comparison, given the proximity and policy similarities between the two. Norway makes an interesting third choice insofar as it is a country with policies that are very different from the other two. (Of course, a necessary condition was also that all countries have accessible microdata on child outcomes, which in practice was a very limiting condition.) While there are differences in policy between Canada and the US, they are less dramatic than the difference between what is available in Norway and what is available in either of the North American countries. This variation increases what can be learned from the cross-country comparisons. While Canada, Norway and the US are all affluent, industrialised countries, it should be noted at the very beginning that the three countries studied do differ significantly in terms of geography and culture.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.009 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".