Investigating the development and coherence of young children’s saving skills
Bibliographic record
Abstract
Reserving resources for future use, or saving, is an ability that emerges around the age of three. However, young children often struggle to save resources. Previous research has examined saving primarily in two domains; token and item saving. However, in day-to-day life children save many other things as well, such as time and space. Children's saving might also be influenced by practices that they and their parents engage in. Thus, the current study investigated: (a) the development of young children's saving, (b) the coherence of saving of four different resources, and (c) the influence of family saving practices on children's saving. Three- to 6-year-old children (N = 98) completed five saving tasks, measuring token, item (marbles and stickers), space, and time saving. Their parents completed two questionnaires tapping into children's saving in everyday life and family saving practices. Children's saving mostly increased with age. Children's saving of abstract resources (tokens, space, and time) cohered, while saving of concrete items (marbles and stickers) cohered. No parental practices predicted children's saving; however, child practices predicted time saving in particular. Broadly, children's saving skills increased with age, with abstract resources (i.e., tokens, space and time) and concrete resources (marbles and stickers) emerging as distinct domains of saving, even after controlling for age and receptive vocabulary scores. This study adds to the existing literature on the development of children's saving and expands our knowledge of how children save different types of resources.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".