'A day in the life': Exploring eating events involving two year old girls and their famillies in diverse communities
Bibliographic record
Abstract
This article reports on a specific aspect of a larger study of 'a day in the life' of five two-and-a-half-year-old girls in families in Canada, Italy, Peru, Thailand and the UK. The larger study involved filming each of the five children in their family contexts for one whole day and studying a number of emerging themes related to the child's development. The focus is on mealtimes and eating. Culture is regarded as a dynamic dimension of the child's socialisation through which family practices around eating (often neglected as a research focus) are explored. Using the concept of an 'eating event', by analogy with a 'literacy event', close examination of video sequences reveal the extent to which children and carers, with differing desires and intentions, negotiate and collaborate to achieve mutually satisfactory ends.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.012 | 0.017 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".