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Record W4413103483 · doi:10.55016/ojs/tsw.v3i1.80280

Voice from the field: Decolonizing subject for more just epistemology

2025· article· en· W4413103483 on OpenAlexaboutno aff

Bibliographic record

VenueTransformative Social Work · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsnot available
Fundersnot available
KeywordsSubject (documents)Field (mathematics)EpistemologySociologyPhilosophyComputer scienceWorld Wide WebMathematics

Abstract

fetched live from OpenAlex

This autobiographical reflection explores the author’s transnational journey of decolonizing social work education, shaped by teaching experiences in Canada and Indonesia. The paper begins with the author’s transformative encounter teaching Anti-Oppressive Social Work Practice at McGill University, where engagement with diverse student identities and critical pedagogy catalyzed a deeper interrogation of positionality, power, and privilege. Upon returning to Indonesia, the author applies decolonial insights to reshape curriculum across three undergraduate courses—Introduction to Social Welfare, Social Work Theories, and Multicultural Social Work—within an Islamic university context. Drawing on literature and classroom practices, the paper critiques the dominance of Eurocentric epistemologies and calls for the integration of Indigenous, Islamic, and local cultural knowledges. Through student-centered learning, critical reflection, field-based assignments, and engagement with concepts like gotong royong and Ubuntu, the author demonstrates how decolonial pedagogy can localize theory, disrupt colonial legacies, and foster culturally grounded social work practices. This work contributes to global dialogues on justice-centered epistemologies in social work education by highlighting the challenges and opportunities of advancing curricular decolonization in postcolonial, religiously rooted contexts.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.945
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0060.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.045
GPT teacher head0.407
Teacher spread0.362 · 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 designNot applicable
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

Citations1
Published2025
Admission routes1
Has abstractyes

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