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Record W7117770867 · doi:10.55016/ojs/tsw.v3i2.80118

Harms and possibilities: Social work doctoral students reflect on social justice pedagogy

2025· article· W7117770867 on OpenAlexaffabout
Amilah Baksh, Alison D. Parnell, Shoshana Pollack, Maxxine Rattner, Andrew Tibbetts

Bibliographic record

VenueTransformative Social Work · 2025
Typearticle
Language
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsYork UniversityWilfrid Laurier University
Fundersnot available
KeywordsSocial workSocial justiceHarmIntersubjectivityProcess (computing)Economic JusticeSocial relation

Abstract

fetched live from OpenAlex

Co-written by four doctoral students and a professor, this article reflects on a novel social work doctoral seminar, “Social Justice Pedagogy.” This course was offered in the 2022 fall term at Wilfrid Laurier University in Ontario, Canada, as part of concerted efforts to acknowledge learning spaces as sites of harm. The mutual draw to this course included all of the authors witnessing, causing, experiencing, or fearing harm in the classroom. This course became about the process and experience of a socially just pedagogical approach. Few PhD social work programs require or even offer a course on the discipline-specific skills of teaching social justice content (Lee et al., 2022; Oktay et al., 2013; Pryce et al., 2011). In this paper, we discuss our motivations for engaging in this novel course and share key insights gained through challenging discussions of racism, gender, and neurodiversity. We engage with themes of intersubjectivity and intersectional identities, attending to process and content in social work education. Further, we engage possibilities related to creating and fostering spaces that emphasize non-hierarchical communication and learning to shape a community of practice among educators. This reflects and reinforces the expectations of social workers to routinely reflect on ethical dilemmas, questions, challenges, and relational dynamics.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies, Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.602
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.011
Science and technology studies0.0310.003
Scholarly communication0.0020.001
Open science0.0010.000
Research integrity0.0010.002
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 head0.081
GPT teacher head0.467
Teacher spread0.387 · 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; both teacher heads agree on what is shown here.

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 routes2
Has abstractyes

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