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Record W2065905361 · doi:10.1080/15423166.2015.1010987

Bringing the Local Back In: Haiti, Local Governance and the Dynamics of Vertically Integrated Peacebuilding

2015· article· en· W2065905361 on OpenAlexaff
Timothy Donais

Bibliographic record

VenueJournal of Peacebuilding & Development · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicPeacebuilding and International Security
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsPeacebuildingTransformative learningPolitical scienceCorporate governancePoliticsRegional integrationPublic administrationSociologyPolitical economyLawManagementEconomics

Abstract

fetched live from OpenAlex

In recent years, ‘the local’ has moved to the forefront of the contemporary peacebuilding debate, as evidenced both by growing scholarly interest in ‘the local turn’ in peacebuilding and by the emphasis on legitimate, inclusive politics in policy discussions surrounding the New Deal for Engagement in Fragile States. What is less clear, however, is how community-level peacebuilding activities can be effectively integrated with longstanding efforts to build peace by building viable, accountable state-level institutions; there remains, in other words, a conceptual and empirical gap between top-down and bottom-up peacebuilding processes. This article draws upon a case study of community-level peacebuilding and violence reduction in the urban slums of the Haitian capital of Port-au-Prince to illustrate the importance of vertical integration for sustainable peacebuilding. It argues that in the absence of explicit linkage — in particular through local-level institutions of governance — with broader statebuilding processes, community-based peacebuilding efforts may ultimately prove to be more palliative than transformative.

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)0.001
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.012
Scholarly communication0.0060.003
Open science0.0000.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.020
GPT teacher head0.279
Teacher spread0.259 · 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

Citations33
Published2015
Admission routes1
Has abstractyes

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