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Record W4205460214 · doi:10.1177/08861099211066338

Creative Writing and Decolonizing Intersectional Feminist Critical Reflexivity: Challenging Neoliberal, Gendered, White, Colonial Practice Norms in the COVID-19 Pandemic

2022· article· en· W4205460214 on OpenAlexaff
Christine Mayor, Shoshana Pollack

Bibliographic record

VenueAffilia · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsReflexivityDialogicSociologyNeoliberalism (international relations)Gender studiesColonialismMetaphorIntersectionalityCritical discourse analysisPolitical sciencePedagogySocial sciencePoliticsIdeology

Abstract

fetched live from OpenAlex

Creative writing during the COVID-19 pandemic can serve as a decolonizing intersectional feminist method for critical self-reflexivity. We share responses to the prompt: “If my therapeutic practice came with a warning label in COVID-19, what would it say?” and provide an analysis of the neoliberalism, whiteness, and colonialism embedded in our creative writing and practice. Engaging in critical self-reflexivity through metaphor carries potential for revealing hidden gendered, racialized, colonial, and neoliberal biases and norms related to social work practice, particularly when done in a collaborative, dialogic manner. We conclude by providing possible creative writing prompts that might be used in social work practice, supervision, and teaching to advance existing practices of self-reflexivity in social work both during and beyond the pandemic.

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)0.037
metaresearch head score (Gemma)0.060
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.198

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0370.060
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0140.057
Scholarly communication0.0170.013
Open science0.0020.015
Research integrity0.0040.008
Insufficient payload (model declined to judge)0.0050.001

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 head0.123
GPT teacher head0.456
Teacher spread0.333 · 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 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

Citations8
Published2022
Admission routes1
Has abstractyes

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