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Record W4409835888 · doi:10.59944/postaxial.v3i2.446

The Impact of Community-Driven Educational Policies on Achieving Equity for Marginalized Students

2025· article· en· W4409835888 on OpenAlex
Lila Nasruden, Nuria del Rey

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Post Axial Futuristic Teaching and Learning · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Learning Practices
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEquity (law)Educational equitySociologyPolitical scienceEconomic growthPedagogyEconomics

Abstract

fetched live from OpenAlex

This study explores the impact of community-driven educational policies on achieving equity for marginalized students. By examining several case studies across diverse educational environments, the research highlights how community involvement in decision-making, culturally relevant curriculum design, and the removal of structural barriers contribute to improved academic performance and social outcomes. Findings indicate that community engagement enhances student participation, academic achievement, and behavior, leading to decreased dropout rates and a positive school climate. Furthermore, the study emphasizes the role of culturally responsive pedagogy in fostering a sense of belonging among marginalized students, thus strengthening the connection between schools and local communities. The results suggest that community-driven policies are a powerful tool for reducing educational disparities and promoting a more inclusive and equitable educational experience for all students. Future research should investigate the long-term sustainability of these practices and their broader implications for global education systems.

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.

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)0.006
metaresearch head score (Gemma)0.020
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.440
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.038
GPT teacher head0.495
Teacher spread0.457 · 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