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Record W4383220194 · doi:10.7202/1100662ar

UNSETTLING CONCEPTIONS OF POWER THROUGH TEACHING AND LEARNING CRITICAL REFLECTION ON SOCIAL WORK PRACTICE

2023· article· en· W4383220194 on OpenAlexvenueaboutno aff
Laura Béres, Trehani M. Fonseka

Bibliographic record

VenueCanadian social work review · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsnot available
Fundersnot available
KeywordsReflection (computer programming)Power (physics)Critical reflectionWork (physics)PedagogyCritical thinkingReflective practiceProcess (computing)SociologyPsychologyEngineering ethicsMathematics educationEpistemologyComputer scienceEngineering

Abstract

fetched live from OpenAlex

Social work education is expected to offer students the opportunity to develop the skills necessary for critical self-reflection as it relates to professional practice. In this paper, we will describe how a model of critical reflection is taught and practiced within our MSW program in a Canadian School of Social Work. As a professor and student within the course, we describe our experience of engaging with the incident that the student used to learn the underlying theories and process of critical reflection. Her experience involved recognizing previously taken-for-granted conceptions of power, which she explored in her final paper for the course. We continued to critically reflect together following completion of the course, and our explorations are presented and expanded upon in this paper as an example of the potential of critical reflection, and as a reminder of the importance to continually reflect upon the complexity of power. Although we began with differing conceptions of power, we agree that power is neither solely ‘bad’ nor ‘good,’ but rather is complex, fluid, and relational. The paper provides an example of the benefits of incorporating opportunities for sustained critical reflection in social work education and concludes with implications for social work practice.

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)0.004
metaresearch head score (Gemma)0.019
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.957
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.004
Science and technology studies0.0100.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.118
GPT teacher head0.469
Teacher spread0.351 · 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

Citations2
Published2023
Admission routes2
Has abstractyes

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