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Record W4220738260 · doi:10.1177/15413446221079590

Co-Creating a Transformative Learning Environment Through the Student-Supervisor Relationship: Results of a Social Work Field Placement Duo-Ethnography

2022· article· en· W4220738260 on OpenAlex
Kimberly A. Calderwood, Larissa N. Rizzo

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Transformative Education · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsTrent University
Fundersnot available
KeywordsTransformative learningPedagogyPsychologySupervisorSociologySocial psychologyManagement

Abstract

fetched live from OpenAlex

In an in-house third-year social work research placement, a duo-ethnography showed that the student–supervisor relationship had far more impact on transformative learning than the assigned placement tasks. A model for co-creating an environment of transformative learning is described, putting student learning and growth at the center. Attributes that contributed to a transformative learning environment included being Trustworthy, Respectful, Engaging, Caring, and Humble. A range of actions within each of these attributes is described. The findings showed that in this context, a crisis-type of disorienting dilemma did not occur. Rather, transformation evolved as part of a learning outcome that included the development of a professional identity as a social worker. Findings suggested the need for further exploration of the role that humility plays in reducing the power imbalance in the student–supervisor relationship. The importance of addressing self-care and avoiding models that risk perpetuating patriarchy in the student-supervisor relationship were highlighted.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.458
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0040.000
Scholarly communication0.0000.001
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 head0.040
GPT teacher head0.381
Teacher spread0.341 · 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