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Record W4404364357 · doi:10.3389/frma.2024.1469377

Bicultural peace pedagogy: opportunities and obstacles

2024· article· en· W4404364357 on OpenAlexaff
Katerina Standish

Bibliographic record

VenueFrontiers in Research Metrics and Analytics · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicPeace and Human Rights Education
Canadian institutionsUniversity of Northern British Columbia
Fundersnot available
KeywordsAotearoaIndigenousBiculturalismPedagogyDecolonizationSociologyTransformative learningIndigenizationCurriculumPolitical scienceGender studiesAnthropologyPsychology

Abstract

fetched live from OpenAlex

This article appreciates decolonization in education, positing bicultural pedagogy as peace pedagogy. It will encapsulate peace education, peace pedagogy, colonization, Indigenous rediscovery, and Indigenization of the curriculum (biculturalism) and then turn to the transformative practice of decolonization in education. The paper seeks to propose a conceptual bridging facet from five core Māori values: wairuatanga, manaakitanga, kotahitanga, whanaungatanga, and rangatiratanga, to Indigenous pedagogy and, finally, to peace pedagogy. The alignment of Indigenous pedagogy and peace pedagogy is an attempt to evaluate the potential of bicultural peace pedagogy as a decolonizing education. The paper finds congruence between Western peace pedagogy and several gaps related to practice and cultural goals. To assist other non-Indigenous knowledge workers (termed Pākehā in Aotearoa/New Zealand) in decolonizing education, this paper has sought to elevate aspects of peace culture that align with Indigenous practices/values.

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)0.030
metaresearch head score (Gemma)0.029
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.158

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0300.029
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0100.014
Scholarly communication0.0140.015
Open science0.0030.022
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0070.001

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 head0.394
GPT teacher head0.510
Teacher spread0.116 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueFrontiers in Research Metrics and AnalyticsSame topicPeace and Human Rights EducationFrench-language works237,207