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Record W7038409736

HOW DOES LEARNING ANTI-RACIST EDUCATION THROUGH CRITICAL PROFESSIONAL DEVELOPMENT AND ARTS-BASED INQUIRY CONTRIBUTE TO TEACHERS’ UNDERSTANDINGS OF THEIR CLASSROOM PRACTICE?

2022· dissertation· en· W7038409736 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity Library (University of Saskatchewan) · 2022
Typedissertation
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSpider Taxonomy and Behavior Studies
Canadian institutionsnot available
Fundersnot available
KeywordsRacismProfessional developmentCritical reflectionQualitative researchTeacher educationReflective practiceHigher educationCritical theoryTeaching method
DOInot available

Abstract

fetched live from OpenAlex

Racism is a significant problem within education. The education system has established institutional hierarchies and perpetuated different forms of racism that restrict the learning experiences of diverse students across Canada. One of the ways that teachers address and disrupt racism is through engaging in critical anti-racist professional development. This study gave teachers the chance to engage in critical anti-racist professional development where they learned about race, racism, and anti-racist education while exploring how their positionalities affect classroom practices. This study used a qualitative arts-based methodology called a/r/tography to create a space where teachers could have deep exploration and understanding of themselves and others by re-imagining lived experiences in and through time through the use of visual art. Combining a/r/tography and anti-racist education together it gave teachers the opportunity to develop awareness of their positionalities, become more critically conscious of their own racialized lenses, and understand how these lenses impact their classroom practices. Through critical artistic reflection on their practice in conjunction with learning anti-racist education strategies, teachers learned to reflect on their practices so as to become more aware of how to disrupt racism and white supremacy within their classrooms.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.169
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.023
GPT teacher head0.269
Teacher spread0.246 · 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 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

Citations0
Published2022
Admission routes1
Has abstractyes

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