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Record W154792440 · doi:10.18584/iipj.2014.5.3.4

Empowering Indigenous Youth: Perspectives from a National Service Learning Program in Taiwan

2014· article· en· W154792440 on OpenAlexvenueno aff
Leemen Lee, Peiying Chen

Bibliographic record

VenueInternational Indigenous Policy Journal · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicService-Learning and Community Engagement
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousEmpowermentPublic relationsGovernment (linguistics)Indigenous educationEconomic growthService-learningEthnic groupPolitical scienceBusinessSociologyPedagogyEconomics

Abstract

fetched live from OpenAlex

Issues related to Indigenous higher education have received more attention in recent years. An important aspect has been the adjustment and development of more inclusive regulatory policies. This study explores the policy-enhancing role of non-profit organizations (NPOs) in empowering Indigenous college students through an analysis of a nationwide service learning program initiated by a NPO based in Taiwan. The findings revealed the important role of NPOs in enhancing government policies by leveraging their knowledge base and resource networking in order to develop a service learning program for Indigenous youth, which aimed to develop their self-confidence and strengthen their ethnic identity. The article identified four themes that are essential for non-profit organizations in designing and implementing empowerment-based programs for Indigenous participants: developing resource networking partnerships, emphasizing responsibility, building effective mutual trust, and sustaining endeavors.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.080

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.003
Scholarly communication0.0030.001
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.039
GPT teacher head0.385
Teacher spread0.346 · 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

Citations12
Published2014
Admission routes1
Has abstractyes

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