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Record W4283698271 · doi:10.1386/ctl_00083_1

Voluntary non-formal teacher professional learning for democratic peacebuilding citizenship education: A participatory approach

2022· article· en· W4283698271 on OpenAlex
Yomna R. Awad

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

VenueCitizenship Teaching and Learning · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicPeace and Human Rights Education
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPeacebuildingCitizenshipDemocracyCitizen journalismNarrativePedagogyProfessional learning communitySociologyProfessional developmentParticipatory action researchPolitical scienceFaculty developmentPublic administrationPoliticsLaw

Abstract

fetched live from OpenAlex

This article presents a six-session course the author developed as an integral part of a doctoral research to explore two small groups of teachers’ initial understandings of democratic peacebuilding citizenship through eliciting their narratives of practice and their emerging understandings after voluntarily participating in this non-formal professional learning initiative. Another aim of the study was to explore how their involvement in the course facilitated their own professional learning. Teacher participants were from different private schools in two relatively contrasting contexts, one in the Greater Cairo Area in Egypt and one in the Greater Toronto Area in Canada. This course sets an exemplary participatory approach to inform future research in teacher professional learning for democratic peacebuilding citizenship education in post-conflict zones, societies transitioning out of violent conflict and relatively democratic societies.

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)0.008
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.088
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0170.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.003
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 head0.045
GPT teacher head0.338
Teacher spread0.293 · 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