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Record W4312168045 · doi:10.5430/ijhe.v11n6p108

Critical Race Theory in English Language Education

2022· article· en· W4312168045 on OpenAlexvenueno aff
Eser Ördem, Ömer Gökhan Ulum, Mustafa Ahmet Cebeci

Bibliographic record

VenueInternational Journal of Higher Education · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Education and Multiculturalism
Canadian institutionsnot available
Fundersnot available
KeywordsCritical race theoryRacismCritical theorySociologyResistance (ecology)White supremacyCritical pedagogyRealmRace (biology)PoliticsCritical consciousnessGender studiesCurriculumAction (physics)EpistemologyPedagogyPolitical scienceLawPhilosophy

Abstract

fetched live from OpenAlex

Racism is still exercised in various social, political and academic spheres and remains to be deconstructed by constituting new discourses. One of these deconstructive discourses has been critical race theory which can be regarded as a productive realm where the oppressed individuals or communities have found the opportunity to address socio-political issues and take collective action where necessary. This study aims to incorporate critical race theory, critical antiracist pedagogy, radical pedagogy, critical consciousness and critical resistance into ELT, EFL and ESL settings and curricula since whiteness and white supremacy have been the dominant discourses in the west perceiving whiteness as Self and blackness as Other. A civil society organization, The Critical Resistance Organization, shown as an example of collective action, was introduced to emphasize how the black movement could produce meaningful changes in a given society. ELT departments in Turkey can adopt an inclusive educational policy and radical pedagogy by taking the issue of racism into consideration to open room for a more liberal, equal and just society. The normalizing discourses regarding whiteness ought to be criticized and displaced by adopting the tenets of critical race theory.

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)0.001
metaresearch head score (Gemma)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.705
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.012
GPT teacher head0.400
Teacher spread0.388 · 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 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

Citations2
Published2022
Admission routes1
Has abstractyes

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