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Record W2950156303

"Anchored in Our Culture, Focused on Our Future": Negotiating Spaces for Somali Women in Toronto through Gashanti UNITY

2018· dissertation· en· W2950156303 on OpenAlexaboutno aff
Muna Ali

Bibliographic record

VenueYork University Digital Library (York University) · 2018
Typedissertation
Languageen
FieldSocial Sciences
TopicJewish and Middle Eastern Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSomaliGender studiesIntersectionalityRacismIslamophobiaOppressionSociologyNegotiationIdentity (music)XenophobiaPolitical sciencePoliticsSocial scienceLaw
DOInot available

Abstract

fetched live from OpenAlex

This research presents and analyses the experiences of second-generation Somali women in Toronto, and argues that there is a significant gap in research about young Somali-Canadian women, and the way they utilize different strategies to manage their multiple and hyphenated identities in order to negotiate social and political spaces for themselves. Through organizations like Gashanti UNITY, with their Anchored in Our Culture, Focused on Our Future motto, young Somali women have taken ownership of their own narratives, through the sharing of their experiences and aspirations. This research seeks to examine and understand specifically the experiences of young self-identified Black, Muslim, Somali, Canadian women, drawing on an interdisciplinary theoretical framework, as well as Intersectionality and Black feminist theory. It highlights ways in which these young women resist and subvert multiple forms of oppression, including, racism, Islamophobia, xenophobia and sexism. This thesis concludes with suggestions for further research that considers the lives and contributions of young Somalis in Canadian society. \n\t \nKeywords: Somali, Women, African, Black, Canadian, Identity, Intersectionality, Black Feminist Thought, race, gender, Islam, islamophobia.

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 score0.085
Threshold uncertainty score0.618

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0580.020
Scholarly communication0.0080.003
Open science0.0010.007
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.000

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 head0.019
GPT teacher head0.241
Teacher spread0.221 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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