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Record W4398210071 · doi:10.1080/10401334.2024.2354454

“Those Darn Kids”: Having Meaningful Conversations about Learner Resistance in Medical Education

2024· article· en· W4398210071 on OpenAlexaff
Tasha R. Wyatt, Lisa Graves, Rachel Ellaway

Bibliographic record

VenueTeaching and Learning in Medicine · 2024
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsUniversity of Calgary
FundersUniformed Services University of the Health Sciences
KeywordsResistance (ecology)Medical educationPsychologyMedicinePedagogyBiology

Abstract

fetched live from OpenAlex

describes the principles professionals should follow when they seek to counter social harm and injustice. Applied to medical education, the principles of professional resistance can help learners and teachers balance the responsibilities to respond to harm and injustice with their roles and responsibilities as health professionals. However, there remains the problem of how educators and leaders can constructively respond to learner acts of resistance. It would seem that many leaders have dismissed learner resistance with variations on "Those Darn Kids!", a complaint that has long been levied at those in younger generations who challenge power and authority. How can productive change in medical education be achieved if learners' complaints are not taken seriously? Rather than dismissal, leaders and educators in these situations need the tools to engage learners in conversations that draw out their concerns.

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)0.007
metaresearch head score (Gemma)0.022
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.744
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.004
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 head0.016
GPT teacher head0.367
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 designOther design
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

Citations5
Published2024
Admission routes1
Has abstractyes

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