MétaCan
Menu
Back to cohort
Record W4390528332 · doi:10.53555/sfs.v10i1.1928

Understanding Stakeholder Perspectives on the Impact of Peace Education in Secondary Schools of Arunachal Pradesh

2023· article· en· W4390528332 on OpenAlexvenueno aff
Eha Migri, Jumri Riba

Bibliographic record

VenueJournal of Survey in Fisheries Sciences · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicPeace and Human Rights Education
Canadian institutionsnot available
Fundersnot available
KeywordsStakeholderInclusion (mineral)Government (linguistics)Peace educationOrder (exchange)Political scienceClass (philosophy)PedagogyQuality (philosophy)Public relationsSociologySocial science

Abstract

fetched live from OpenAlex

The goal of the study is to learn what the instructors in Arunachal Pradesh secondary schools think about the inclusion of peace education in the modules. It sought to investigate their perspectives, difficulties, and willingness to incorporate practices of peace education into their pedagogy. In order to achieve this, the researchers evaluated the quality of peace education in two secondary schools and one semi-government residential school in the lower and Dibang Valley using both quantitative and qualitative approaches. They used tactics like group talks, observations, and interviews to interview 12 individuals from these districts. In order to gather information, the researchers spoke with class teachers and principals at each school, held interviews with district stakeholders, and generally engaged themselves as responsible and exemplary citizens. The results showed that educators and interested parties stressed how crucial it is to include peace education in the modules. They believed it could reduce discords among students and contribute to shaping.

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)0.006
metaresearch head score (Gemma)0.006
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 score0.015
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0150.005
Scholarly communication0.0050.002
Open science0.0010.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.534
GPT teacher head0.400
Teacher spread0.134 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Survey in Fisheries SciencesSame topicPeace and Human Rights EducationFrench-language works237,207