INVESTIGATING THE MULTIMODALITY OF CHILDREN AND YOUTH
Bibliographic record
Abstract
Capturing lived childhoods without decontextualizing their meaning and still providing information needed by policy-makers and practitioners is a pressing challenge for contemporary researchers. In this paper we provide information to open up such a dialogue via a range of tools we have utilized when investigating well-being. We interrogate bio-socio-ecological approaches to human development to provide relatively holistic pictures of the lived experience of childhood. We utilize various methodologies within this approach to determine what they transactionally facilitate at each level. At the bio-psychological level, for example, controlled, psychologically valid, psychosocial stress procedures expose hormonal responses, yielding valuable information about individual differences in physiological stress reactivity. At the level of the psychological self within a social ecology, we systematically observe children and youth in naturalistic, environmental transactions with the aid of visual methodologies such as Day in the Life filming, and invite the children and their parents and youth to share their reflections on their lived context via focused discussions and interviews. In this paper we discuss new ways of integrating research findings by suggesting Sameroff’s (2010) unified theory as an interpretive framework for research within the field of child and youth care.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".