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Record W2898279984 · doi:10.3167/arcs.2018.040110

Perspectives from the Ground

2018· article· en· W2898279984 on OpenAlexaboutno aff
Jaymelee J. Kim

Bibliographic record

VenueConflict and Society · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Security, and Conflict
Canadian institutionsnot available
Fundersnot available
KeywordsBureaucracyTransitional justiceIndigenousColonialismEthnographyEconomic JusticePolitical scienceGovernment (linguistics)SociologyCriminologyLawPoliticsAnthropologyEcology

Abstract

fetched live from OpenAlex

While traditionally underrepresented in transitional justice studies, anthropological study of culture, ethnography, and processes can contribute valuable insight into colonial bureaucracies and dynamics of power. This article uses an ethnographic approach and a colonial bureaucratic violence theoretical foundation to analyze negative perceptions of transitional justice at the ground level. Participants included facilitators, government officials, nonprofit organizations, and Indigenous community members; research occurred during implementation of transitional justice (2011–2014) for a period of 12 months. Specifically, I argue that the relationship between transitional justice and colonial bureaucratic violence encourages negative views of transitional justice. Instead, ethnographic data first reveals that bureaucratic processes within transitional justice challenge Indigenous identities. Second, Indigenous survivors in British Columbia, Canada, largely view transitional justice on a continuum of colonial bureaucratic violence. Using a colonial bureaucratic violence framework, this article provides insight and nuance into perceptions of transitional justice at the local level.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.064
Threshold uncertainty score0.126

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0250.034
Scholarly communication0.0140.008
Open science0.0010.009
Research integrity0.0030.009
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 head0.044
GPT teacher head0.313
Teacher spread0.269 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations7
Published2018
Admission routes1
Has abstractyes

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