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Record W4205634046 · doi:10.22215/etd/2021-14697

Data Colonialism in Canada: Decolonizing Data Through Indigenous data governance

2021· dissertation· en· W4205634046 on OpenAlexaboutno aff
Donald Leone

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicGeographic Information Systems Studies
Canadian institutionsnot available
Fundersnot available
KeywordsColonialismIndigenousDecolonizationSovereigntyCorporate governanceContext (archaeology)Political sciencePolitical economySociologyGeographyPoliticsLawArchaeologyManagementEcology

Abstract

fetched live from OpenAlex

In 1991, the Government of Canada mandated the Royal Commission on Aboriginal Peoples (RCAP) to investigate the relationship between First Nations, Inuit, and Mtis peoples of Canada, the Crown, and citizens of Canada. The call for the RCAP was the result of centuries of colonization of Indigenous peoples, that included mistreatment, subjugation, and paternal oversight in Canada which led to unrest, resistance, and violence 1 . The resulting five-volume report by the RCAP published in 1996 tells the haunting history of injustice, misunderstanding, and the struggles of Canada's Indigenous peoples both historically and in the post-colonial settler society context, highlighting vast inequities across the economic, social, and political situations of Indigenous communities and peoples across Canada. It also describes what a new relationship based on mutual respect and trust with First Nations, Inuit, and Mtis peoples might look like 2 .

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Open science
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.634
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.003
Open science0.0080.003
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 head0.115
GPT teacher head0.364
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.

Study designNot applicable
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

Citations3
Published2021
Admission routes1
Has abstractyes

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