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Record W2509632072 · doi:10.29173/alr136

Reconciliation and Conflict: A Review of Practice

2011· review· en· W2509632072 on OpenAlexvenueaboutno aff
Emily Snyder

Bibliographic record

VenueAlberta Law Review · 2011
Typereview
Languageen
FieldSocial Sciences
TopicCambodian History and Society
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)CommissionDissentEvent (particle physics)Isolation (microbiology)SociologyConflict resolutionSpace (punctuation)Political sciencePublic relationsLawHistoryPoliticsComputer science

Abstract

fetched live from OpenAlex

In this article I provide a review of two connected events. The first is the conference "Prairie Perspectives on Indian Residential Schools, Truth and Reconciliation," which was held in June 2010 in Winnipeg, Manitoba. This conference was just one of many concurrent events taking place at the Truth and Reconciliation Commission of Canada's first national event. Specific themes and aspects of the conference are covered here. Secondly, I parallel my discussion of the conference to my experiences with the national event - experiences can be complex and do not happen in isolation from the broader context around them. Overall, I argue that while the conference and the national event made some meaningful contributions to ongoing dialogue about reconciliation in Canada, it is clear that understanding how to deal with and discuss the conflict that arises from discussions of residential school, "race relations," and reconciliation more broadly is an ongoing learning experience. I offer some recommendations concerning how conflict could be better dealt with at future conferences and national events. Reconciliation processes can be more effective if there is not only space for dissent but, most importantly, that mechanisms are in place for encouraging productive discussions about the conflict that arises and that will continue to arise.

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)0.004
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.616
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.095
GPT teacher head0.396
Teacher spread0.301 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations1
Published2011
Admission routes2
Has abstractyes

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