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Record W4400770546 · doi:10.29173/assert75

Deep in the heart of Texas

2024· article· en· W4400770546 on OpenAlexvenueno aff
ArCasia James-Gallaway

Bibliographic record

VenueAnnals of Social Studies Education Research for Teachers · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicCritical Race Theory in Education
Canadian institutionsnot available
Fundersnot available
KeywordsStatus quoWhite (mutation)SociologyWhite supremacyPoliticsCritical race theorySubordination (linguistics)StatuteInclusion (mineral)Political scienceDiversity (politics)Civil rightsGender studiesPedagogyRacismLaw

Abstract

fetched live from OpenAlex

From my position as a Black social studies teacher educator and interdisciplinary historian of education who calls Texas home, I explore in this essay how critical educators might consider what some of Texas’s most recent “diversity, equity, and inclusion (DEI)” statutes signify about the effectiveness of critical Black social studies teachers’ work thus far. I underline what Nobel laureate Toni Morrison said about the heightened restriction she faced given her writing: that it can often indicate our work is indeed disrupting the ongoing, systemic project of white domination and antiBlack subordination. Then, I highlight how Black educators of the Jim Crow era navigated political atmospheres comparable to the one in which Texas educators, among others, now find themselves. Looking back at these educators’ subversive practices, which sought to undermine the status quo of white supremacy and antiBlackness, I suggest how their work might guide those engaged in similar projects today.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.037
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0200.020
Scholarly communication0.0110.005
Open science0.0010.006
Research integrity0.0020.008
Insufficient payload (model declined to judge)0.0140.001

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 head0.380
GPT teacher head0.637
Teacher spread0.257 · 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 designQualitative
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

Citations1
Published2024
Admission routes1
Has abstractyes

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