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De kloof overbruggen met herstelrechtelijke reacties op misstanden in organisaties: lessen uit het proces van overgangsgerechtigheid op de Canadese kostscholen

2025· article· W4417181637 on OpenAlexaboutno aff
Laura Hein

Bibliographic record

VenueTijdschrift voor Herstelrecht · 2025
Typearticle
Language
FieldPsychology
TopicForgiveness and Related Behaviors
Canadian institutionsnot available
Fundersnot available
KeywordsRestorative justiceTransitional justiceContext (archaeology)Economic JusticeHarmInterpersonal communication

Abstract

fetched live from OpenAlex

Bridging the gap with restorative justice responses to abuses in organisations: lessons from the Canadian Residential School’s transitional justice process Restorative justice and transitional justice are increasingly recognized as complementary approaches. While they have traditionally operated in different domains, restorative justice at the interpersonal and transitional justice in post-conflict or large-scale human rights violation contexts, their integration offers promising pathways for more holistic justice processes. This article contributes to the broader debate on their synergies by focusing specifically on the context of abuses in organisations. These abuses often reflect systemic and enduring patterns of harm that affect large numbers of victims, requiring justice responses that address not only micro-level interpersonal healing but also macro-level structural transformation. This makes it a particularly interesting context for examining how restorative and transitional justice can intersect. Using the Canadian case of residential schools as an example, the article explores how transitional justice practices and frameworks such as acknowledgement, truth-seeking, (symbolic) reparations, and guarantees of non-repetition, can deepen and extend restorative justice practices in institutional settings.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.602
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0020.004
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0030.001
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0120.001

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 head0.013
GPT teacher head0.321
Teacher spread0.309 · 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 designNot applicable
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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