Why we still need the term ‘Young Carer’
Bibliographic record
Abstract
Previous research on young carers has provided data on prevalence, the tasks performed, the impacts on the carer, and the supports they require. However, some in the disability rights movement argue that the numbers of young carers and the negative impacts of caring have been exaggerated, and that the children’s rights approach serves to undermine the rights of disabled and/or ill parents. The findings from exploratory research in Ireland suggest that it is not parental illness and/or disability that is a cause for concern, but instead levels of support to and awareness of young carers. It is argued that the term young carer should continue to be used and that services should be developed in Ireland specifically for young carers.
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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 | 0.020 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.032 |
| Scholarly communication | 0.008 | 0.028 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.014 | 0.020 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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".