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Challenges for Peacebuilding and Citizenship Learning in Colombia

2019· article· en· W2910849092 on OpenAlex
Ángela María Guerra-Sua

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMagis Revista Internacional de Investigación en Educación · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicPeace and Human Rights Education
Canadian institutionsUniversity of Toronto
FundersUniversity of Toronto
KeywordsPeacebuildingDissenting opinionCitizenshipCurriculumInjusticeAgency (philosophy)Social injusticeSociologyDemocracyPolitical scienceCross-cultural psychologyEngineering ethicsEnvironmental ethicsPedagogySocial scienceLawPolitics

Abstract

fetched live from OpenAlex

Some education practices can impede learning democratic citizenship agency by reinforcing injustices or omitting dissenting perspectives. Other practices may help address conflict issues through problem-posing inquiry activities. This literature review explores the ways social sciences’ curriculum practices can select knowledges that enhance peace or exacerbates violence. Considering peace and conflict theories, I highlight the limitations and possibilities for peacebuilding of Colombia’s citizenship and social sciences’ curricula. Also, I discuss the ways certain social studies curriculum decisions (selections and omissions) may reproduce violence, injustice and passivity. Finally, I discuss how certain practices may develop critical citizenship capacities to handle conflicts.

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)0.001
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 score0.843
Threshold uncertainty score0.784

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.037
GPT teacher head0.332
Teacher spread0.295 · 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