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Record W4413893775 · doi:10.1177/02645505251371031

‘Our people could more accurately be described as social workers’: Professional identity, practice standards and regulation in Irish probation

2025· article· en· W4413893775 on OpenAlexaff
Vivian Geiran

Bibliographic record

VenueProbation Journal · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsTrinity College
Fundersnot available
KeywordsIrishIdentity (music)SociologySocial workProfessional standardsSocial identity theoryPsychologyPublic relationsSocial psychologyCriminologyPolitical scienceManagementLawSocial groupEconomics

Abstract

fetched live from OpenAlex

In 2018 the Irish Probation Service introduced a requirement that applicants for positions as probation officers must be registered social workers. Five years later, in 2023, that requirement was removed. That latter decision, as well as other organisational changes and current legislative proposals have the potential to weaken the erstwhile strong link between probation and social work in Ireland and more importantly to reduce overall practice standards and organisational effectiveness. This article considers the frequently ambiguous connection between social work and probation in Ireland, under a number of headings, including history, professional identity, registration and regulation, language, and education. Issues currently impacting or likely to have an adverse impact on that connection between social work and probation, and practice standards, will be discussed and the unfulfilled promise and potential that social work continues to offer Irish probation explored. In the context of wider pressures on the Irish criminal justice system, specifically prison overcrowding, and the role of the Probation Service in response, the piece will also discuss how the current less than optimal situation can be turned around to positive effect.

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 imitation

Not 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.

metaresearch head score (Codex)0.021
metaresearch head score (Gemma)0.036
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.124
Threshold uncertainty score0.246

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.036
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0170.054
Scholarly communication0.0160.008
Open science0.0020.015
Research integrity0.0040.009
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.077
GPT teacher head0.491
Teacher spread0.414 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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