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Record W4410039959 · doi:10.1080/10911359.2025.2498398

Field notes and reflections: Why isn’t social work addressing antisemitism?

2025· article· en· W4410039959 on OpenAlexaff
Leslie Yaffa, Annette Poizner

Bibliographic record

VenueJournal of Human Behavior in the Social Environment · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicGerman legal, social, and political studies
Canadian institutionsAlgoma University
Fundersnot available
KeywordsAntisemitismSocial workField (mathematics)SociologyWork (physics)PsychoanalysisPsychologyPolitical scienceHistoryLawJudaismArchaeology

Abstract

fetched live from OpenAlex

This article critically reflects on the social work profession’s inadequate response to rising antisemitism, particularly following the events of October 7, 2023. Drawing on scholarly research, media reports, and personal and professional experiences, the authors highlight the systemic exclusion of Jewish perspectives in social work discourse, education, and DEI (Diversity, Equity, and Inclusion) frameworks. Key issues include the misapplication of “white privilege” to Jewish individuals, the omission of antisemitism from DEI agendas, the uncritical use of biased educational materials, and the marginalization of Jewish narratives in discussions surrounding the Israeli-Palestinian conflict. The authors also explore the impact of the BDS movement and rising radicalization on campuses, which has created an increasingly hostile environment for Jewish students and practitioners. They call for a re-examination of social work’s ethical commitments, advocating for the inclusion of Jewish voices, recognition of contemporary antisemitism, and the cultivation of cultural humility. The piece serves as a call to action for the social work community to align its practices with its professed values of justice, equity, and inclusion for all marginalized groups, including Jews.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.653
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.085
GPT teacher head0.412
Teacher spread0.326 · 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 designObservational
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

Citations2
Published2025
Admission routes1
Has abstractyes

Explore more

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