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Record W4281986861 · doi:10.1177/01605976221107093

Building Peace in Northern Ireland: Hopes for the Future

2022· article· en· W4281986861 on OpenAlex
Seán Byrne, Karine Levasseur, Laura E. Reimer

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueHumanity & Society · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicPeacebuilding and International Security
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsPeacebuildingPublic administrationPolitical scienceCivil societyPoliticsNorthern irelandProtestantismSociologyEconomic growthLawEconomics

Abstract

fetched live from OpenAlex

Since the Good Friday Agreement of 1998, over 2 billion Euros have been poured into Northern Ireland for peacebuilding. This article presents the hopes and experiences of workers in CSOs funded by either or both funds, development officers, and civil servants employed by the funders. They confirm that peacebuilding and reconciliation projects funded by the European Union (EU) Peace and Reconciliation Fund and the International Fund for Ireland (IFI) have positively contributed to the peace process in Northern Ireland. Civil Society Organizational (CSO) projects support peacebuilding, reconciliation, and greater cooperation between the Protestant and Catholic communities. This study explored the perceptions of 120 respondents working with these funders. They indicated that designated peacebuilding funding promotes bridging, needs to be balanced, and is important to building the peace dividend and that local knowledge, practices, and skillsets should be built into the funding process. The politics of post-Brexit Northern Ireland means that understanding how to best fund peacebuilding and reconciliation is critical. At time of writing, tensions have risen.

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.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.578
Threshold uncertainty score0.999

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 studies0.0030.000
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 head0.026
GPT teacher head0.315
Teacher spread0.290 · 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