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Record W4213255603 · doi:10.1093/bjsw/bcac038

Assessment as a Site of Anti/Oppressive Social Work Practice: Negotiating with Power and the De/Professionalisation of Social Work

2022· article· en· W4213255603 on OpenAlexaff
Eunjung Lee

Bibliographic record

VenueThe British Journal of Social Work · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSocial workSociologyContext (archaeology)GovernmentalityNegotiationPower (physics)Public relationsEngineering ethicsSocial sciencePolitical scienceLawPolitics

Abstract

fetched live from OpenAlex

Abstract Social work practice starts with an effort to understand clients-in-context, a task which involves a process of assessment. Whilst social workers often assess clients-in-systems, rarely do they consider the social worker-in-systems as part of the client’s context. Guided by Foucault’s concepts of disciplinary and biopolitical power and related constructs of ‘Panopticism’ and ‘homo oeconomicus’, this article interrogates how the social worker’s observational gaze in assessment has become veiled in practice. Using a critical review method, the author examines how Foucault’s notion of a ‘faceless gaze’ has been increasingly intensified by the use of information technology in ‘common assessment’, thereby transforming the fundamentals of assessment from understanding the client for ‘care’ to ‘managing risk’ in neoliberal governance. This article historicises and politicises temporal discourses of social work assessment and illustrates how the worker’s embodied knowledge of assessment as a governing apparatus may solidify and/or endanger the social work profession. Locating assessment as a site of social in/justice, this critical review on the inevitable workings of power in assessment invites social workers to re-think the boundaries of de/professionalisation and to critically reflect on and re-imagine everyday institutional practices in social work assessment.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.268
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0160.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.018
GPT teacher head0.361
Teacher spread0.344 · 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 teacher head, not a consensus.

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

Citations10
Published2022
Admission routes1
Has abstractyes

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