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Record W3036568525 · doi:10.1080/01436597.2020.1761253

Gaps in knowledge about local peacebuilding: a study in deficiency from Jos, Nigeria

2020· article· en· W3036568525 on OpenAlexaff
Reina C. Neufeldt, Mary Lou Klassen, John Danboyi, J. W. Dyck, Mugu Zakka Bako

Bibliographic record

VenueThird World Quarterly · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicPeacebuilding and International Security
Canadian institutionsWilfrid Laurier UniversityUniversity of Waterloo
Fundersnot available
KeywordsPeacebuildingContext (archaeology)Political scienceSociologyPublic relationsPublic administration

Abstract

fetched live from OpenAlex

The emphasis on local or hybrid efforts in peacebuilding literature brings front and centre the importance of being rooted within a particular context, with leadership and vision for social change and justice proffered by local actors. This is the same emphasis found in development literature and a necessary foundation for transformation. Scholars and practitioners nevertheless also note a role for outsiders in supporting local efforts (eg Lederach in 2005). Yet a significant challenge arises for outsiders, and to some extent local actors: how do you know what was tried or is underway that you might support or from which you might learn? This paper reports findings from a collaborative research project that examined the gap between the practice of peacebuilding locally and internationally available ‘knowledge’ via publications produced on local peacebuilding in Jos, Nigeria, between 2001 and 2008. It identifies a staggering gap between efforts and knowledge in the form of publications. The paper discusses the implications of the findings in terms of what it means for outsiders when thinking about helping resource local transformation efforts.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.490
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.028
GPT teacher head0.327
Teacher spread0.299 · 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 designObservational
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

Citations5
Published2020
Admission routes1
Has abstractyes

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