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Record W4413751643 · doi:10.3138/ecf.2024-0064

Open Educational Resources for a More Just Romanticism

2025· article· en· W4413751643 on OpenAlexvenueno aff
Leila Walker

Bibliographic record

VenueEighteenth-Century Fiction · 2025
Typearticle
Languageen
FieldComputer Science
TopicOpen Education and E-Learning
Canadian institutionsnot available
Fundersnot available
KeywordsRomanticismLiteratureArtPsychology

Abstract

fetched live from OpenAlex

Efforts to diversify the field of Romanticism, long overdue, have intensified recently, and many Romanticist organizations now sponsor programmes aimed at amplifying Black and Brown voices. Most of these efforts have focused on content: how to present Romanticism as a global movement and include non-white authors in our anthologies and syllabi. While these much-needed changes address some of the field’s traditional blind spots, they do little to materially benefit our most vulnerable students or to address the structural barriers that maintain Romanticism’s exclusionary status quo. Open educational resources, or OERs, are one way to begin productively transforming the way the study of Romanticism is taught and reproduced. This article explores how Romantic philosophies and contemporary conceptions of justice might resonate with efforts to transform the material experience of teaching and learning through the open pedagogy movement.

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)0.003
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesOpen science
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.999
Threshold uncertainty score0.139

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.015
Scholarly communication0.0150.021
Open science0.0010.012
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0410.008

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 head0.019
GPT teacher head0.313
Teacher spread0.293 · 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.

Study designNot applicable
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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