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Record W1931505475

Understanding Sustainability Education: A Community-Based Experience

2014· article· pt· W1931505475 on OpenAlexaff
Ranjan Datta, Nyojy U. Khyang, Hla Kray Prue Khyang, Hla Aung Prue Kheyang, Mathui Ching Khyang, Jebunnessa Chapola

Bibliographic record

VenueLA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) · 2014
Typearticle
Languagept
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsIndigenousParticipatory action researchSustainabilityTraditional knowledgeCitizen journalismEnvironmental ethicsEnvironmental educationPoliticsPolitical scienceSociologyPublic relationsEconomic growthPedagogyAnthropologyEcologyLaw
DOInot available

Abstract

fetched live from OpenAlex

Sustainability education policies are widely focused on modern technologies, green profits, and development projects in many Indigenous communities. However, there has been minimal attention given to critical areas such as: Indigenous world views, spiritual and relational practices, culture, lands, and revitalization. This imbalance, combined with the destruction and lack of recognition to Indigenous knowledge (systems), suggests that Indigenous environmental education policies are still in a state of adolescence as a field of academic inquiry. The present study examines how an Indigenous community understands sustainability and analyzes these understandings in relation to the literature on the politics of nature as well as Indigenous and postcolonial studies. This research followed a relational Participatory Action Research (PAR) research approach with a focus on the researchers’ relational accountabilities and obligations to study participants and site.

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)0.011
metaresearch head score (Gemma)0.011
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 score0.040
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0400.022
Scholarly communication0.0100.011
Open science0.0030.020
Research integrity0.0060.010
Insufficient payload (model declined to judge)0.0080.001

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 head0.057
GPT teacher head0.309
Teacher spread0.252 · 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

Citations18
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueLA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas)Same topicIndigenous Health, Education, and RightsFrench-language works237,207