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Record W4396839002 · doi:10.15402/esj.v9i2.70812

Participatory, Multimodal Approaches to Child Rights Education in Global Contexts: Reflections on a Study with Schoolchildren in Uganda and Canada

2023· article· en· W4396839002 on OpenAlexafffundvenueabout
Shelley Jones, Kathleen Manion

Bibliographic record

VenueEngaged Scholar Journal Community-Engaged Research Teaching and Learning · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicChildren's Rights and Participation
Canadian institutionsRoyal Roads University
FundersRoyal Roads University
KeywordsCitizen journalismChild rightsParticipatory action researchPolitical scienceHuman rightsSociologyPedagogyGender studiesAnthropologyLaw

Abstract

fetched live from OpenAlex

Globally, we have much to learn about fulfilling international child education rights, particularly in times of crisis, as evidenced during the global COVID-19 pandemic. Although the right of children to know their rights is enshrined in the United Nations Convention on the Rights of the Child, and other documents, such as the African Charter on Rights and Welfare of the Child, child rights are rarely introduced to children as part of their formal learning experience in school, because children are deemed unable to understand the concepts of rights (and responsibilities) (Alderson, 2008; Jerome, 2018). This lack of child-rights education means children are denied opportunities for empowerment: e.g., awareness and knowledge needed for self-advocacy, advocacy for other children with respect to the ability to claim and exercise their rights (Covell et al., 2017; Wabwile, 2016). Drawing on a case study conducted in Uganda and Canada, this paper discusses how participatory, empowering, multimodal, and contextually-responsive/sensitive approaches to child rights education enables children to engage meaningfully in learning about their rights.

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)0.408
metaresearch head score (Gemma)0.112
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.465
Threshold uncertainty score0.895

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.4080.112
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.2130.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.227
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 head0.262
GPT teacher head0.445
Teacher spread0.183 · 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; both teacher heads agree on what is shown here.

Study designQualitative
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
Published2023
Admission routes4
Has abstractyes

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