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Record W2581946544 · doi:10.7202/1082338ar

The Treatment of Aboriginal Children in Canada: A Violation of Human Rights Demanding Remedy

2021· article· en· W2581946544 on OpenAlexvenueaboutno aff
Clara Filipetti

Bibliographic record

VenueFirst Peoples Child & Family Review An Interdisciplinary Journal Honouring the Voices Perspectives and Knowledges of First Peoples · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
Fundersnot available
KeywordsHuman rightsAccountabilityGovernment (linguistics)Action (physics)PopulationPolitical scienceQuality (philosophy)Public administrationLaw and economicsLawSociologyPublic relations

Abstract

fetched live from OpenAlex

This article examines two problems faced by the Canadian population: the current conditions of Aboriginal children and the lack of concrete course of action established to improve the dire conditions and lack of access to basic resources. This article proposes that a human rights framework can be utilized to address the disparities between Aboriginal and non-Aboriginal children in Canada. An integrated human rights framework acknowledges the complexity of the relationship between universal, natural and legal rights and provides a system of accountability to track the quality and success of the improvements made by the government of Canada. Due to the complex and systematic nature of the problem, a human rights framework provides a way to supplement the treaties and agreements that the government of Canada has often used as reasons for not taking responsibility. This paper concludes that an integrated human rights framework is an effective way to address the significant gaps between Aboriginal and non-Aboriginal children in terms of access and funding for social, health and educational services.

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)0.008
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.095
Threshold uncertainty score0.688

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0140.011
Scholarly communication0.0030.001
Open science0.0030.004
Research integrity0.0040.008
Insufficient payload (model declined to judge)0.0030.000

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 head0.012
GPT teacher head0.319
Teacher spread0.307 · 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 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

Citations3
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueFirst Peoples Child & Family Review An Interdisciplinary Journal Honouring the Voices Perspectives and Knowledges of First Peoples→Same topicIndigenous Health, Education, and Rights→French-language works237,207→