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Record W2022822358 · doi:10.2304/rcie.2012.7.2.160

Multi-level Research on Youth Participation in the Haitian Reconstruction

2012· article· en· W2022822358 on OpenAlexaff
Gary Pluim

Bibliographic record

VenueResearch in Comparative and International Education · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicTourism, Volunteerism, and Development
Canadian institutionsInstitute for Christian StudiesUniversity of Toronto
Fundersnot available
KeywordsNegotiationSociologyContext (archaeology)Public relationsPoliticsEducational researchPolitical sciencePedagogyGender studiesSocial scienceLaw

Abstract

fetched live from OpenAlex

Research in comparative and international education routinely encounters exceptional research conditions. In this article, the author explores the particular issues he faced in his research on multi-level youth programs of the Haitian reconstruction. Through a vertical analysis of internationally sponsored programs, this study required special attention to working in a cross-cultural, politically fragile environment. In this article, he highlights connections with several other multi-level studies in fragile states which are also featured in this issue of RCIE. However, his focus is upon those issues that are particular to conducting research in post-earthquake Haiti. These issues include the roles of researcher and participants, the impact of discourses of security, and negotiating cross-cultural issues such as language, power, and notions of participation. This article also positions his research by including an overview, a theoretical framework, the socio-political context, and a detailed description of methodology and methods.

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 score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0080.005
Scholarly communication0.0040.002
Open science0.0010.006
Research integrity0.0010.001
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 head0.675
GPT teacher head0.598
Teacher spread0.077 · 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

Citations1
Published2012
Admission routes1
Has abstractyes

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