A comparative study of children's fears and fear displays in Canada and Australia: What are they afraid of and how do they show it?
Bibliographic record
Abstract
While a number of emotions are considered to be innate or present from a very early age, the way they are understood and displayed is determined by social and cultural as well as biological factors. Adults or "expert others" from the environment in which children live can facilitate young children's development of emotion understanding and display. Yet adults do not always recognise emotion and emotion display in children. This paper discusses a cross-cultural study of the emotion of fear. In Canada and in Australia caregivers were asked to name fears that preschool-aged children (3-5 year olds) experience, and to describe how these children show fear. While some differences were found in fears and fear displays, a much greater difference was found in their incidence. For example, 55 % of Canadian caregivers reported young children to have a fear of loud noises, whereas only 11 % of Australian caregivers reported this fear. Forty-five per cent of Canadian caregivers reported that children display fear through their body language, while only 10 % of Australian caregivers reported this fear display. Issues of similarity and difference in fear and fear display as reported by caregivers in both countries are examined and recommendations made for early childhood pedagogical practice.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".