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Record W2995049760 · doi:10.1097/acm.0000000000003136

Postmodernism and Medical Education

2019· review· en· W2995049760 on OpenAlexaff
Rachel Ellaway

Bibliographic record

VenueAcademic Medicine · 2019
Typereview
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsSouth Health CampusUniversity of Calgary
Fundersnot available
KeywordsPostmodernismIdeologyEpistemologySkepticismOppressionSociologyContext (archaeology)PoliticsHegemonyLawPhilosophyPolitical science

Abstract

fetched live from OpenAlex

Postmodernism emerged in the mid-20th century in the context of postwar Europe where philosophers and artists were taking increasingly skeptical and critical positions on modernist thinking and practice. Postmodernism is not a single organized and coherent perspective; it is a collection of related philosophies, techniques, models, and perspectives that take a skeptical and critical perspective on thinking and practice. Ontologically, postmodernism is predicated on the belief that power and its underlying meanings, manipulations, and ideologies shape our ability to act in and think about the world. Epistemologically, postmodernism seeks to explore and understand underlying meanings, structures, and intents in the world and to consider alternative explanations and interpretations for them. Axiologically, postmodernism can be used to analyze value in the context of inequity, oppression, and hegemony within social systems and structures. Due to the lack of coherence within postmodernist thought, there is no one definitive methodological stance. However, there are many postmodernism-informed methodological stances, which vary both in terms of what is examined and how it is examined. As an approach within medical education, postmodernist perspectives can help to expose and analyze the political and ideological positioning of much of what is done, particularly in the interests of addressing systemic problems of justice and equity. It is somewhat paradoxical that postmodernism allows researchers to challenge the nature and expression of truth, and it allows them to problematize and deconstruct the ideologies and agendas of those who are themselves challenging the nature and expression of truth.

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)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.082

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0060.063
Scholarly communication0.0070.008
Open science0.0010.007
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0070.001

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 head0.085
GPT teacher head0.481
Teacher spread0.396 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations22
Published2019
Admission routes1
Has abstractyes

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