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Record W4413301977 · doi:10.25071/2292-6739.255

Redress and Reconciliation for Indigenous Peoples in the Form of Apologies: An Inadequate and Abysmal Procedure that Supports Settler Colonialism

2025· article· en· W4413301977 on OpenAlexaffvenueabout
Natasha Latina

Bibliographic record

VenueContingent Horizons The York University Student Journal of Anthropology · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicAsian Geopolitics and Ethnography
Canadian institutionsLakehead University
Fundersnot available
KeywordsRedressIndigenousColonialismPolitical scienceGender studiesEthnologyHistorySociologyLawEcologyBiology

Abstract

fetched live from OpenAlex

To reach redress and reconciliation with Indigenous Peoples, establishments such as the Catholic Church as well as the Canadian Government decided to issue “apologies;” however, these attempts are unauthentic as they support settler colonial ideals, and further promote the marginalization of Indigenous Peoples. This paper critiques current attempts of redress and reconciliation for Indigenous Peoples by contending these “apologies” are insincere. Drawing on various frameworks provided by scholars such as Borrows, Palmater, Corntassel and Holder, as well as Tavuchis and James, this paper analyzes apologetic attempts made by the Catholic Church, former Canadian Prime Minister, Stephen Harper (2008), and Pope Francis (2022) to argue that “apologies” are not only inadequate forms of reconciliation, but also insinuate absolute disregard and disrespect towards all Indigenous Peoples. Most importantly, this paper claims that the Canadian Federal Government must implement strategies of reconciliation with Indigenous Peoples by including them in policy-making decisions.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.289
Threshold uncertainty score0.817

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.024
GPT teacher head0.323
Teacher spread0.300 · 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 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
Published2025
Admission routes3
Has abstractyes

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