The Developing Habitus of the Anti‐Social Behaviour Practitioner: From Expansion in Years of Plenty to Surviving the Age of Austerity
Bibliographic record
Abstract
Specialist anti‐social behaviour units are common within social housing providers, with many established in response to the policies of the New Labour governments of 1997–2010. These units now find themselves operating in a different political and financial environment. Following the English riots of 2011, the Coalition government, whilst imposing budgetary cuts across the public sector, called on social housing providers to intensify their role in tackling disorder. This article explores the habitus or working cultures within anti‐social behaviour units post‐New Labour. It does so through empirical research conducted in the aftermath of the English riots. The research finds that practitioners view their work as a core function of social housing provision. They have developed an understanding of human behaviour, which crosses the criminal and social policy fields with a wide skillset to match. A number of factors including national policy, community expectations, and multi‐partnership engagement influence their dynamic working culture.
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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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.020 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".