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Record W7024709171

Stuck at the border of the reserve: Self-idenatity and authentic identity amongst mixed race First Nations women

2010· dissertation· en· W7024709171 on OpenAlexaboutno aff

Bibliographic record

VenueThe Atrium (University of Guelph) · 2010
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicDust and Plasma Wave Phenomena
Canadian institutionsnot available
Fundersnot available
KeywordsIdentity (music)Context (archaeology)PerceptionSocial identity theoryRace (biology)Poison controlSuicide preventionDomestic violence
DOInot available

Abstract

fetched live from OpenAlex

The lowered self-esteem of First Nations people is evident in the disparities in health that exist in comparison with the rest of the Canadian population. High risk behaviors such as alcohol and drug use, and poor decisions relating to health and wellness are the outcome of decades of negative perceptions of self brought on by the lateral violence of colonialism. This research demonstrates how different determinants of First Nations identity (legal and policy based, social and culturally based definitions, and the self-identification ideology) interplay and influence a sense of authenticity which informs self-worth and the ability to realize health and wellness for twelve First Nations women on Manitoulin Island. First Nations identity is multi-layered and for women who only have one First Nations parent, and who often have Bill C-31 Indian status, identity becomes complicated and painful. Using life histories, the research participants demonstrate that an authentic identity is difficult to navigate because of the stigmatization they feel by non First Nations people for being a First Nations woman, and also the lateral violence they experience in their communities for being "bi-racial", not growing up on their reserve, not knowing language and culture, and often having either Bill C-31 Indian status or no status at all. The medicine wheel is used to explore this topic and a Nanabush story provides the context to understand it.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.619
Threshold uncertainty score1.000

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.006
GPT teacher head0.218
Teacher spread0.212 · 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 designObservational
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
Published2010
Admission routes1
Has abstractyes

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