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Record W4383823236 · doi:10.1086/725728

Attempting Equity in Classroom Practice

2023· article· en· W4383823236 on OpenAlexaboutno aff
Whitney M. Hegseth

Bibliographic record

VenueThe Elementary School Journal · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicEducation Methods and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsEquity (law)AutonomySituatedPsychologyInequalityPedagogyEthnographyMathematics educationSocial psychologySociologyPolitical science

Abstract

fetched live from OpenAlex

This article reports on findings from an ethnographic and comparative study examining interactions between educational systems and mutual respect in classrooms. I define mutual respect as the work of intervening on power asymmetries typically found in classrooms—both between teachers and students, and among students—by way of according children increased equality, autonomy, and equity. I partnered with four elementary schools, situated across two systems (i.e., International Baccalaureate [IB] and Montessori) and two national contexts (i.e., Washington, DC, and Toronto). Analysis of observation and video-cued focus group data revealed the following: IB and Montessori teachers differed in how they attempted equity in practice, and, relatedly, they differed in how they understood equity to interact with other dimensions of mutual respect (i.e., equality, autonomy). These differences between the systems held constant across two national contexts. This study contributes to ongoing conceptualizations of equity, educational systems, and the potential relationship between the two.

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)0.009
metaresearch head score (Gemma)0.017
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.024
Scholarly communication0.0070.006
Open science0.0010.017
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.156
GPT teacher head0.538
Teacher spread0.382 · 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

Citations4
Published2023
Admission routes1
Has abstractyes

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