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Record W3181339115 · doi:10.1080/14623943.2021.1948825

Critical reflection: a student’s perspective on a ‘pedagogy of discomfort’ and self-compassion to create more flexible selves

2021· article· en· W3181339115 on OpenAlexaff
Kristen Robinson

Bibliographic record

VenueReflective Practice · 2021
Typearticle
Languageen
FieldPsychology
TopicMindfulness and Compassion Interventions
Canadian institutionsThe King's UniversityWestern University
Fundersnot available
KeywordsReflection (computer programming)Transformational leadershipPerspective (graphical)CompassionPedagogyPsychologyCritical reflectionIdeologyReflective practiceCritical pedagogyExperiential learningSociologySocial psychologyComputer science

Abstract

fetched live from OpenAlex

In this paper, I explore Fook’s model of ‘Critical Reflection on Practice’ and how discomfort and vulnerability can become an impediment to authentic critical reflection and transformational learning. This paper is written from my perspective, as an emerging social worker to uncover how the integration of Boler’s ‘pedagogy of discomfort’ and practices of self-compassion into Fook’s model of critical reflection can heighten awareness, deepen reflective possibilities, and create more flexible selves. Including a ‘pedagogy of discomfort’ into critical reflection can serve to guide practitioners and students through the vulnerable process of uncovering cognitive, affective, and habitual patterns linked to dominant ideologies and hegemonic forces. The inclusion of self-compassionate teachings into the model of critical reflection better equips practitioners and students with tools to withstand the emotional labour that results from discomfort and reflection. With these tools, practitioners can reconstruct their experiences with new insights to engage in transformational change for personal and professional growth.

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)0.016
metaresearch head score (Gemma)0.021
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: none
Teacher disagreement score0.016
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.021
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0080.042
Scholarly communication0.0150.014
Open science0.0030.011
Research integrity0.0080.019
Insufficient payload (model declined to judge)0.0030.001

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 head0.051
GPT teacher head0.508
Teacher spread0.457 · 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

Citations15
Published2021
Admission routes1
Has abstractyes

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