Bibliographic record
Abstract
Welfarisation is another technology of government through which female illicit drug users are governed. It is the process that constructs individuals or groups as needing social support, or that constitutes them as unworthy of it. Governments themselves create welfarisation through the maintenance of structural inequalities, social and economic marginalisation and its ‘management’. Certain ‘needy’ or ‘at-risk’ groups of individuals are targeted for welfarisation or ‘soft policing’ through formal and informal social control mechanisms (Worrall, 2001). Welfarisation is in principle, benevolent, and may involve the provision of support with social funds, housing, training, jobseeking or childcare. It may prove to be a lifeline for some individuals, but programmes of welfare have long been identified as having (darker) mechanisms of surveillance and social control embedded within them. This relates to Foucault's concept of the ‘carceral continuum’ and his view that regulatory techniques permeate ‘a whole series of institutions … well beyond the frontiers of criminal law’ involving doctors, social workers and educators (1991 [1975], p 297). Drawing on Foucault’s work, Cohen (1985, p 3) argues that liberal capitalist countries such as the UK, Canada and the US all have ‘social control systems’ embedded in their programmes of ‘welfare’ and ideologies of treatment. The idea that policies of welfare also operate as mechanisms of control and surveillance particularly over marginalised groups of individuals has been explored and developed by various writers across a range of disciplines and subjects (see Parton, 1991, on child protection; Carlen, 1988, on young women in care; Carrington, 1993, on juvenile girls; Phoenix, 1999, on sex workers). Interventions into the lives of women who use illicit drugs presented as policies and practices of welfare (concerned with their wellbeing) are often experienced as intrusive, coercive and punitive (see Chapter Seven, pp 238–245 and 253–256). Mechanisms of control and surveillance, including practices of welfare, also serve to enforce gendered expectations of behaviour and to reinforce inequalities of gender. The technology of welfarisation is closely related to that of normalisation discussed in the following chapter (see Part Three, pp 142–144). This chapter investigates the surveillance and regulation of drugusing women through welfare and social work policies and practices.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.309 | 0.132 |
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".