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Record W4391780127 · doi:10.3138/jvme-2023-0152

“Going From Strength to Strength”: Delving into Professional Identity Formation of Veterinary Curriculum Leaders: A Narrative Inquiry

2024· article· en· W4391780127 on OpenAlexvenueno aff
Elizabeth Armitage‐Chan, Melinda Bell, Martin Cake, Kate Cobb, Heidi Janicke, Sarah Kelly, Emma K. Read, Sheena Warman

Bibliographic record

VenueJournal of Veterinary Medical Education · 2024
Typearticle
Languageen
FieldHealth Professions
TopicVeterinary Practice and Education Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumNarrativeIdentity (music)Medical educationPedagogyProfessional developmentPsychologySociologyMedicineArt

Abstract

fetched live from OpenAlex

Curriculum leaders, individuals with responsibility for an institution's veterinary curriculum, are student-oriented, want to make a difference, and prioritize teaching and pedagogy in their work. However, as they work to enhance curriculum development, they experience tensions in their role. This study built on previous quantitative findings, and aimed to explore further how curriculum leaders respond to tensions, and how their identity is constructed and supported in a way that means they can thrive in their role. Using self-determination theory and narrative identity as conceptual frameworks, nine curriculum leaders were interviewed about their experiences. Narrative inquiry methodology enabled in-depth interpretations to be drawn about identity influences and participants' responses to conflict and dissonance. Curriculum leader identity was defined as being student-centered, change-oriented, valuing both clinical (particularly general practice), and pedagogical expertise while engaging in hard work and service to achieve pedagogical goals. Participants were skilled in leading change and had developed skills and personal attributes for this. Leading change involved experiences of conflict and tension that were personally meaningful, evoking feelings of identity dissonance that were characterised by either emotional resilience or disaffection and frustration. This response depended on social identity influences, including opportunities to network with like-minded peers, recognition of achievements from influential others, institutional advocacy for change, and support for advanced pedagogical training.

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)0.002
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient 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 score0.089
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.003
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 head0.332
GPT teacher head0.566
Teacher spread0.234 · 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 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

Citations2
Published2024
Admission routes1
Has abstractyes

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