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Record W7162788846 · doi:10.1093/jhuman/huaf036

Pluralized Knowledge in Critical Human Rights Education Design: Confronting Orthodox Understandings of the Canon, Disciplinarity, and Expertise

2025· article· en· W7162788846 on OpenAlexfundno aff
Tamara Baldwin, Maxwell Bogpene, Jenny H Peterson

Bibliographic record

VenueJournal of Human Rights Practice · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicPeace and Human Rights Education
Canadian institutionsnot available
FundersUniversity of British Columbia
KeywordsExperiential learningPluralConversationMetaphorRedevelopmentPower (physics)Human rights

Abstract

fetched live from OpenAlex

Abstract Through an exploration of the planning, implementation, assessment, and redesign of an interdisciplinary undergraduate course on human rights, this article provides empirical insight into a range of pedagogical tools that contribute to the aims of critical human rights education (CHRE), including experiential or activist components. With its overall goal of exposing students to plural understandings and operations of power, the course engaged in three distinct practices: regularly bringing ‘the canon’ into conversation with ‘the critical’, challenging norms and power related to disciplinarity, and epistemic challenges to the notion of ‘expertise’. These practices are evidenced throughout the article, drawing on examples of course design, class activities, and student projects conducted with community partners. Analysis of these tools and their impact on student learning in ways that align with the goals of CHRE reveals two important lessons in pedagogical design: holistic planning and braiding. The redevelopment of the course illustrates the importance of paying significant attention to the ways in which different elements of a course are interdependent—challenging ‘sequential’ models of pedagogical design and instead encouraging the metaphor of ‘braiding’ in course design and delivery. These lessons emerge as particularly true in regard to the experiential elements of the course and are important in challenging tensions between the ‘critical’ vs ‘practical’ schools of human rights education. The article concludes with a discussion of the challenges of engaging in CHRE within the confines of higher education institutions.

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)0.002
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.086
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.001
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 head0.079
GPT teacher head0.478
Teacher spread0.399 · 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.

Study designTheoretical or conceptual
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

Citations0
Published2025
Admission routes1
Has abstractyes

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