Bibliographic record
Abstract
This editorial forms part of a themed issue on vulnerability and risk across the life course. The six articles in this issue explore the issues that arise when key individuals are not considered competent to assess risks and make decisions. The articles by Bailey and her colleagues and by Cott and Tierne focus on older people whose competence is affected by cognitive impairment, Clarke and Edge and Eyles consider issues that affect babies and young children and Spencer and Thing and Ottesen explore the way older children or young people manage risk. All the articles show that risk is contested in terms of who should manage it and how it is defined. The articles indicate that relatives play a key role in assessing risk and making decisions on behalf of older people with cognitive impairment, babies and young children. Drawing on an empirical study of older people with cognitive impairment Cott and Tierne show that relatives are reluctant to intervene and take over decisions, as they do not want to undermine the independence of their elderly relative. They engage in a balancing act tolerating the normal hazards of everyday life but taking action when they identified new and worrying dangers or ‘red flags’. In the case of young children, as Clarke's analysis of articles in one high circulating mass print Canadian magazine, Chatelaine, mothers are expected to identify emerging behavioural and mental health problems and take expert advice to minimise harmful outcomes. However, expert advice on the nature and management of risk is contested. Edge and Eyles indicate that experts in Canada justified their decision to ban the chemical Bisphenol A from the babies bottles on evidence of potential harm, but the decision context was shaped by the ‘pro-health’ lobby campaign that appealed to emotions of the public emphasising the innocence and vulnerability of babies. The articles in this issue indicate the limit of the rational expert approach to risk. As Bailey indicates in a review of the literature on the care of older people with dementia, practitioners have tended to be risk averse, locating the risk in the older person and not in their social setting. Spencer and Thing and Ottesen show that young people see themselves as competent risk takers and have the self-confidence to resist adult and experts’ definition of risk. For these young people, the meaning of risk is embedded in everyday life and to enjoy life and have fun they have to balance time, energy and risks.
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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 | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.005 | 0.011 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".