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Record W2589286239

Indigenous Life Courses, Racialized Gendered Life Scripts, and Cultural Identities of Resistance and Resilience

2016· dissertation· en· W2589286239 on OpenAlexaboutno aff
Angele Alook

Bibliographic record

VenueYorkSpace (York University) · 2016
Typedissertation
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsResistance (ecology)IndigenousResilience (materials science)Scripting languageGender studiesSociologyComputer science
DOInot available

Abstract

fetched live from OpenAlex

The aim of this research project was to understand the cultural identity of young Indigenous adults living between on-reserve, off-reserve rural settings, and the city. The secondary research question examined the gendered experiences of family, school, and work in this process. I interviewed men and women, 16 from the city of Edmonton, and 15 living in Wabasca, Alberta. This study uses my brand of Indigenous Sociology, in which I combine Cree Indigenous research methodologies, Indigenous feminism, and a life course approach. As background, I lay out the complex geographic, demographic, historical and colonial context of the migration experiences, and show that Indigenous peoples continue to live under a colonial regime that geographically and racially divides us. \nFindings from interviews reveal cultural identity is based on family relations. Key themes explored are: the child as central to family and community; family as central to building healthy relations and cultural identity; and positive and negative understandings of community. I explore a theory on bouncing among family relations and locations, while balancing family, school and work. One of the key findings of this study is how extended family networks provide for moral support, financial support, and childcare support for those that choose to complete an education and become steadily employed. I present Indigenous models of family as a form of resistance and resilience to colonialism, and that healthy family relations are built in different locations. \nI present the interview findings on school and work choices. I outline the colonial structures of education which impact access to schooling and funding, which are divided along geographic and racial lines. I examine specific factors that acted as barriers and facilitators to achievements in school and work. I finish by explaining that community members must contend with racialized gendered life scripts along their life courses. Specifically, Indigenous women must contend with life scripts that expect a fate of early childbearing and poverty. Indigenous men contend with a life script that expects them to drop out of high school and enter unskilled jobs in the oil industry. To challenge these life scripts Indigenous men and women demonstrate their agency by making choices for education, and choices to find skilled jobs. \nI conclude by stating that Indigenous men and women develop an identity based on their resistance and resilience against racist and gendered structural institutions in school and work. I suggest that social policies for Indigenous peoples on education, training, and employment must incorporate an Indigenous model of lifelong learning to combat racialized gendered life scripts. This will allow for a holistic approach where relations to family and community are integral to learning, and Indigenous understandings of the life course can be easily integrated.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.911
Threshold uncertainty score0.177

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.020
Scholarly communication0.0040.002
Open science0.0010.005
Research integrity0.0000.001
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 head0.021
GPT teacher head0.310
Teacher spread0.289 · 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 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

Citations1
Published2016
Admission routes1
Has abstractyes

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