Practitioner Emotions in Penal Voluntary Sectors: Experiences from England and Canada
Bibliographic record
Abstract
Abstract Mixed economies of welfare have seen increasing numbers of service users funnelled into voluntary, rather than statutory sector services. Many service users with (complex) human needs now fall within the remit of ill-researched voluntary organisations that are rarely social work led. Voluntary sector practitioners comprise a large and rising proportion of the social services workforce, but their experiences have received minimal analysis. Despite the importance of emotions across the helping professions, voluntary sector practitioners’ emotional experiences are largely unknown. We address this gap, using an innovative bricolage of original qualitative data from England and Canada to highlight how ‘emotions matter for penal voluntary sector (PVS) practitioners across diverse organisational roles, organisational contexts, and national jurisdictions’. We examine the emotions of paid and volunteer PVS practitioners relating to their (i) organisational contexts and (ii) relationships with criminalised service users. Problematising positive, evocative framings of ‘citizen participation’, we argue that continuing to overlook voluntary sector practitioners’ emotions facilitates the downloading of double neo-liberal burdens—‘helping’ marginalised populations and generating the funds to do so—onto individual practitioners, who are too often ill-equipped to manage them.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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 teacher head, 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".