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Record W2178087559

A Sociocultural Approach to Teaching about Racism

2015· article· en· W2178087559 on OpenAlexvenueno aff
Tuğçe Kurtiş, Phia S. Salter, Glenn Adams

Bibliographic record

VenueSound Ideas (University of Puget Sound) · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicCritical Race Theory in Education
Canadian institutionsnot available
Fundersnot available
KeywordsRacismSociocultural evolutionSociologyAnti-racismEpistemologyGender studiesAnthropologyPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

Drawing upon previous research which finds that a sociocultural approach to teaching about racism results in increased consciousness about racism and support for antiracist policies (Adams et al., 2008), we designed and implemented a tutorial consistent with this approach in our Cultural Psychology courses. The tutorial presented undergraduate students with media images involving stereotypical representations of people from various racially marginalized groups. Students indicated how much racism they perceived in each image and discussed different conceptions of racism, reasons for variation in racism perception, and potential consequences of exposure to these images. The instructor then presented findings from social and cultural psychological research addressing key issues in student discussions. This presentation reinforced a systemic conception of racism and encouraged students to consider the extent to which learning about racism from the target’s perspective can contribute to efforts towards social justice. Student responses were mostly consistent with the general idea that learning about racism matters, and more specifically with the proposal that a pedagogy emphasizing a sociocultural approach to racism can serve as a force for social justice.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.138
Threshold uncertainty score0.742

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.045
GPT teacher head0.335
Teacher spread0.290 · 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.

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

Citations1
Published2015
Admission routes1
Has abstractyes

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