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Record W6925537138 · doi:10.17613/feesm-3sj85

Toward a Brutalist Turn in Education

2025· article· en· W6925537138 on OpenAlexaff

Bibliographic record

VenueKnowledge Commons (Lakehead University) · 2025
Typearticle
Languageen
FieldMedicine
TopicMicrobial Natural Products and Biosynthesis
Canadian institutionsUniversity of AlbertaUniversity of British Columbia
Fundersnot available
KeywordsCharacter (mathematics)Mode (computer interface)Philosophy of educationEducation theory

Abstract

fetched live from OpenAlex

As a kind of 'raw materialism', we argue that brutalism constitutes a useful analytic or figure with which to delink thinking from under the orthodoxies of educational thinking in the Global North. Our intention in this essay is not to offer yet another concept, critique, solution to, or survey of things gone wrong in the history of education and schooling. We propose that if a 'brutalist turn' is possible in education, it might be thought along two lines of import. The first might pertain to the ways in which infrastructure both orders and informs upon the character of pedagogical life. A second aspect of the brutalist turn might involve a different approach to educational analysis that adopts from the experimental mode of brutalism a host of new strategies for educational thought and practice. While not comprehensive, such strategies might harness the ideas of exposure, desubjectification, and molecular revolution as a fulcrum for relaunching education from under its contemporary lethargy.

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)0.013
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.070

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.001
Science and technology studies0.0090.084
Scholarly communication0.0120.012
Open science0.0010.006
Research integrity0.0040.011
Insufficient payload (model declined to judge)0.0040.001

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 head0.023
GPT teacher head0.259
Teacher spread0.236 · 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 designTheoretical or conceptual
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

Citations0
Published2025
Admission routes1
Has abstractyes

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