Bibliographic record
Abstract
Introduction Asset-based welfare has provoked attention as one of the most innovative ideas in recent public policy. Policies to promote assetbased welfare can take a variety of forms (Kelly and Lissauer, 2000). One of the most prominent schemes centres on paying young people a capital grant once they reach a certain age. One reason why young people command attention is that they are the section of the population that have least access to assets (Banks and Tanner, 1999), and so tackling this points towards initiatives directed at the young. However, there is as yet little evidence of the attitudes of young people themselves to this kind of policy. The attitudes of young people are important for the current and future design of this policy, since capital grant policies can be constructed in a variety of ways. Grants can differ over the amount of money that is paid out, the restrictions that are imposed on the use of such grants, as well as ways of funding the grants. The success of any scheme will depend on how young people choose to make use of their grants. Investigating their views helps anticipate which policies are likely to be a success and which issues need to be faced when revising and developing the policy. This chapter presents findings from 11 focus groups held in Sheffield and London between 9 February 2004 and 16 June 2004 on the attitudes of young people to different models of capital grants. We seek to draw implications from these focus groups not just for the immediate development of policies like the Child Trust Fund (CTF), but also, more tentatively, for wider debates about the future of the welfare state. We find that young people react favourably to capital grant schemes, and like the idea of the CTF. Looking beyond the framework of current policy, our focus groups were in favour of a more generous CTF, although they wanted it to be a complement rather than a substitute for existing forms of welfare provision. The chapter is structured as follows. First, by way of context we discuss how asset-based welfare appears to have been concentrated thus far in the US, Britain, Canada and Australia (countries sometimes referred to as ‘Anglo-Saxon capitalism’), but why it may still have implications for other welfare states.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".