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Record W2760831804 · doi:10.5206/cie-eci.v46i2.9319

Citizenship Education in a Fragile State: NGO Programs for Democratic Development and Youth Participation in Haiti

2017· article· en· W2760831804 on OpenAlexaffvenue
Gary Pluim

Bibliographic record

VenueComparative and International Education · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicTourism, Volunteerism, and Development
Canadian institutionsLakehead University
Fundersnot available
KeywordsCitizenshipAgency (philosophy)Context (archaeology)DemocracyYouth studiesPolitical scienceSociologyCurriculumIdeologyGender studiesSocial sciencePedagogyPoliticsLaw

Abstract

fetched live from OpenAlex

This research centres on NGO citizenship education programs in Haiti to better understand youth experiences, outcomes, and perceptions of democracy. The findings from this study illustrate how programs from Western-based NGOs with liberal democratic traditions typically construct citizenship education in relation to the individual agency of the learners, whereas youth living in the context of fragility note the prerequisite for stable social structures as a foundation for citizenship. Through multi-dimensional analyses, this article highlights the importance of historical perspectives, the value of comparing disparate societies, and the necessity to explicate social locations in cross-cultural research. The concluding proposition states that not only does context matter in international research, but illustrates specifically how context affects youth participants subject to curriculum emanating from competing ideological environments. The issues explored here are among the key concerns for the future of comparative and international research in a globalizing and diverse world.

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 score0.025
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0060.002
Scholarly communication0.0020.001
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.124
GPT teacher head0.426
Teacher spread0.302 · 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
Published2017
Admission routes2
Has abstractyes

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