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Reshaping political ideology in social work: A critical perspective

2017· article· en· W2736669030 on OpenAlexaff
Filipe Duarte

Bibliographic record

VenueAotearoa New Zealand Social Work · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsCarleton University
Fundersnot available
KeywordsIdeologySociologyMarxist philosophySocial philosophyPoliticsEpistemologySocialismSocial scienceArticulation (sociology)Environmental ethicsSocial relationPolitical scienceLawCommunism

Abstract

fetched live from OpenAlex

INTRODUCTION: The article contends that social work is politically constructed, that its values, principles and commitments are deeply shaped by ideology through the political dimension at all levels of social work intervention, and that social work needs not only to embrace, but also to reshape its political ideology, discourse and political movements.APPROACH: It is argued that the articulation of social work values and principles are an expression of ideology, and that political ontology of social workers’ lives precedes their epistemological and methodological choices. From this premise, the article claims that socialism informs progressive social work values, and that a materialist analysis can influence our understanding of social problems and social relations within deregulated capitalist societies.CONCLUSIONS: Firstly, this article synthesises the Marxist approach of ideology and its relations with ideology in social work. Secondly, it draws out the key insights about the so-called “radical” or “structural” perspective in social work, and the commitments and challenges of its advocates. Finally, it explores and proposes insights on the political ideology of social work for the 21st century.

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)0.019
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.022
Threshold uncertainty score0.158

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.003
Science and technology studies0.0200.134
Scholarly communication0.0150.010
Open science0.0020.008
Research integrity0.0050.008
Insufficient payload (model declined to judge)0.0030.000

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 head0.069
GPT teacher head0.424
Teacher spread0.355 · 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 designTheoretical or conceptual
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

Citations16
Published2017
Admission routes1
Has abstractyes

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