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Record W4396775067 · doi:10.1017/aee.2024.13

Relationality in Indigenous Climate Change Education Research: A Learning Journey from Indigenous Communities in Bangladesh

2024· article· en· W4396775067 on OpenAlexaff
Ranjan Datta

Bibliographic record

VenueAustralian Journal of Environmental Education · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change, Adaptation, Migration
Canadian institutionsMount Royal University
Fundersnot available
KeywordsIndigenousTraditional knowledgeReciprocity (cultural anthropology)SociologyEnvironmental ethicsPsychological resilienceIndigenous educationEducation for sustainable developmentEnvironmental resource managementPolitical scienceSustainable developmentSocial scienceSocial psychologyEcologyPsychologyLaw

Abstract

fetched live from OpenAlex

Abstract This article explores my relational learning reflections with the Laitu Khyeng Indigenous community in the Chittagong Hill Tracts (CHT), Bangladesh, focusing on Indigenous perspectives on climate change education. Implementing a relational theoretical framework, I share my reflections on relational learning in this research as part of being accountable to the Indigenous community. Through exploring Indigenous land-based climate change research, five central themes emerge Indigenous land rights, relationship with the environment, community-led relationality as collaboration, intergenerational relational knowledge and relationality as ethical reciprocity. The findings explore the intrinsic connection between Indigenous communities and their ancestral territories, emphasising the significance of upholding Indigenous sovereignty over land for sustainable adaptation to climate change. In this article, I highlight the importance of relational learning as a form of education, fostering resilience rooted in preserving traditional practices and spaces. Relationality with the environment is central to Indigenous climate education, promoting understanding and reciprocity with the land. In my learning, I learned that community dynamics and collaborative learning are essential for effective climate education, emphasising collective action and diverse perspectives. In relational learning, inter-generational knowledge transmission ensures the preservation and sharing of traditional land-based knowledge across generations, forming the foundation for sustainable adaptation strategies. Ethical engagement and reciprocity guide research interactions, emphasising mutual respect and cultural sensitivity. By centring Indigenous perspectives and knowledge systems, this study advocates for community-led approaches to climate change education, fostering resilience and environmental stewardship within Indigenous communities.

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)0.021
metaresearch head score (Gemma)0.014
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 score0.027
Threshold uncertainty score0.112

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0270.023
Scholarly communication0.0130.009
Open science0.0020.021
Research integrity0.0030.007
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 head0.248
GPT teacher head0.411
Teacher spread0.163 · 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

Citations15
Published2024
Admission routes1
Has abstractyes

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