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Creating Inclusive Reconciliation and Reporting Spaces with Children: Valuing Their Stories

2023· book-chapter· en· W4399090616 on OpenAlexaboutno aff
Caitlin Mollica

Bibliographic record

VenuePolicy Press eBooks · 2023
Typebook-chapter
Languageen
FieldSocial Sciences
TopicChildren's Rights and Participation
Canadian institutionsnot available
Fundersnot available
KeywordsSociologyPsychology

Abstract

fetched live from OpenAlex

The conflict stories of children are integral to meaningful reconciliation following violence. Increasingly, children’s stories and their identities have come to reflect a broader peace narrative within transitional justice. Yet often the participation of children is retold and shared through mechanisms that are inaccessible and disconnected from their reconciliation experiences. As such, children’s interactions with reconciliation practices are often static, heavily mediated and unresponsive, particularly when their stories are used as symbols for a political agenda. Only three Truth and Reconciliation Commissions (TRCs) – Canada, Sierra Leone, and Timor-Leste – have created accessible conflict narrative reports that facilitate children’s political engagement in reconciliation. This chapter considers the role of child-friendly reports in delivering reconciliation processes that recognize children as political actors rather than embodiments of peace. It argues that TRCs have an obligation to produce accessible reports that fulfil the state’s obligation to children as citizens. By normalizing accessible reporting standards, opportunities are created for inclusive international processes with not for children even beyond the reconciliation space.

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.623
Threshold uncertainty score0.967

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.110
GPT teacher head0.359
Teacher spread0.249 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreOther

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 routes1
Has abstractyes

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