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Record W4415001582 · doi:10.1002/crq.70008

Practice Insight: Adapting Peacebuilding Dialogue Methodologies to City‐Resident Relations and Inclusive Policymaking in Calgary, Canada

2025· article· en· W4415001582 on OpenAlex

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueConflict Resolution Quarterly · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicPeacebuilding and International Security
Canadian institutionsUniversity of OttawaUniversity of Calgary
Fundersnot available
KeywordsPeacebuildingAgency (philosophy)Diversity (politics)Structure and agencyDialogical self

Abstract

fetched live from OpenAlex

ABSTRACT This case study presents a project in which peacebuilding dialogue methodologies were adapted for use in municipal‐level dialogue sessions that took place in Calgary, Canada in late 2022 and early 2023. The authors found that using this approach built trust among cross‐sectoral participants and facilitators, resulted in greater diversity during recruitment, strengthened participant agency that led to City‐wide transformations and built connections between groups, sectors and geographical areas that had not regularly come into contact. Additionally, the project generated insights into how peacebuilding methodologies can be adapted and applied within contexts of non‐armed societal conflicts in the Global North, particularly in areas thought to suffer from marginalization or a deficit of trust in local governing bodies—in this case, setting the stage for a novel form of multi‐track dialogue that facilitates inclusive, community‐engaged municipal policymaking.

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)0.002
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.913
Threshold uncertainty score0.687

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.053
GPT teacher head0.398
Teacher spread0.344 · 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