Bibliographic record
Abstract
As we have seen, normative patterns of youth transition have extended during the last 40 years, and for most young people leaving home and acquiring the traditional signifiers of adult life have been considerably delayed. However, young people leaving care are exceptions to this trend, and accelerated transitions to adulthood are more likely for this group (Wade and Dixon 2006). Government policy has aimed to delay transitions and improve support for young people in the period leading up to and after leaving care. 1 But there is considerable variation in outcomes between local authorities and between different groups of young people; those with disabilities, mental health issues and offending behaviour tend to fare badly compared with care leavers with less complex needs. The number of children and young people in care in England has increased in recent years, with 67,050 children being looked after in 2012, an increase of 13 per cent compared with 2008. Consequently, the number of young people leaving care has also increased, and whilst the majority of these are aged 18 and over, some leave care at 16 or 17 (DfE 2012a; 2012c). Many of these young people return to live with parents or with other responsible adults; however, in 2011 a quarter of 16-year-olds and nearly 40 per cent of 17-year-olds moved into what is euphemistically know as ‘independent living’ but can instead be a frightening and isolating experience. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.011 |
| Insufficient payload (model declined to judge) | 0.112 | 0.020 |
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".