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Record W2775037993 · doi:10.26522/brocked.v26i2.605

What Informs and Inspires the Work of Equity Minded Teachers

2017· article· en· W2775037993 on OpenAlexfundvenueaboutno aff
Stephanie Tuters

Bibliographic record

VenueBrock Education Journal · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicTeacher Education and Leadership Studies
Canadian institutionsnot available
FundersUniversity of Toronto
KeywordsEquity (law)Equity theoryWork (physics)PsychologyPublic relationsSociologyPolitical scienceEconomic growthEconomics

Abstract

fetched live from OpenAlex

This article explores teachers’ reasons for engaging in equity work. Although multiple bodiesof literature discuss teaching for equity from different perspectives, little empirical data existsabout what informs or motivates people to teach for equity. This study aims to help fill thatgap in existing research with the purpose of informing professional development and trainingfor practicing teachers hoping to or attempting to engage in equity work, and for encouragingand motivating other educators in beginning to engage in equity work. Data was gatheredthrough interviews with 15 teachers from three large school boards in Southern Ontario.Findings illustrate that participants were motivated to engage in equity work because ofpersonal experiences with inequity, witnessing other people experience inequities, and learningabout inequities in school. Three key findings stand out with regards to their utility forprofessional development and training: all participants spoke of critical incidents whichcompelled them to do equity work; emotional struggles were associated with their work, yetthey remained hopeful in the possibility of change regardless of what they had experienced;finally, the nature of the equity work that participants chose to undertake was directly relatedto the nature of their experience with in/equity.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.309
Threshold uncertainty score0.999

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 studies0.0020.000
Scholarly communication0.0010.001
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 head0.155
GPT teacher head0.446
Teacher spread0.291 · 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

Citations11
Published2017
Admission routes3
Has abstractyes

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