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Record W1807775112 · doi:10.1186/1472-698x-2-6

Community based rehabilitation: a strategy for peace-building

2002· article· en· W1807775112 on OpenAlexaff
William Boyce, Michael Koros, Jennifer Hodgson

Bibliographic record

VenueBMC International Health and Human Rights · 2002
Typearticle
Languageen
FieldMedicine
TopicEthics and Legal Issues in Pediatric Healthcare
Canadian institutionsQueen's University
Fundersnot available
KeywordsPeacekeepingContext (archaeology)EmotiveState-buildingCapacity buildingPolitical sciencePublic relationsDemocracyState (computer science)Intervention (counseling)Public administrationSociologyPoliticsPsychologyLawComputer sciencePsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Certain features of peace-building distinguish it from peacekeeping, and make it an appropriate strategy in dealing with vertical conflict and low intensity conflict. However, some theorists suggest that attempts, through peace-building, to impose liberal values upon non-democratic cultures are misguided and lack an ethical basis. DISCUSSION: We have been investigating the peace-building properties of community based approaches to disability in a number of countries. This paper describes the practice and impact of peace-building through Community Based Rehabilitation (CBR) strategies in the context of armed conflict. The ethical basis for peace-building through practical community initiatives is explored. A number of benefits and challenges to using CBR strategies for peace-building purposes are identified. SUMMARY: During post-conflict reconstruction, disability is a powerful emotive lever that can be used to mobilize cooperation between factions. We suggest that civil society, in contrast to state-level intervention, has a valuable role in reducing the risks of conflict through community initiatives.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.875
Threshold uncertainty score0.650

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.156
GPT teacher head0.443
Teacher spread0.287 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations23
Published2002
Admission routes1
Has abstractyes

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