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Record W4254896847 · doi:10.32920/ryerson.14648325

Young diaspora Somali women's navigation of intersectional identities in online social media spaces

2021· preprint· en· W4254896847 on OpenAlexaffabout
Samira Warsame

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicSocioeconomic Development in MENA
Canadian institutionsToronto Metropolitan UniversityUniversity of Toronto
Fundersnot available
KeywordsSomaliMainstreamIntersectionalityGender studiesDiasporaSociologyThe artsIdentity (music)NarrativeSocial mediaMedia studiesPolitical scienceVisual artsAestheticsArt

Abstract

fetched live from OpenAlex

Using Crenshaw’s work on intersectionality, this research examines how young Somali women have used the arts to challenge negative mainstream media discourse regarding the Black, Muslim and Somali identities. This research, similar to Crichlow's work on narrative sharing in the classroom space being used to amplify the voice of the oppressed and the marginalized, finds that young Somali women are using the arts interact with their intersectional identities and share them in online spaces. Social media has provided room for them to use and amplify their own voices which inevitably challenges negative representations promoted by mainstream media outlets while interacting with their intersectional identities. Using 6 Somali women from the arts communities in two of the major Somali-populated cities in the West; Toronto, Canada, and Minneapolis, USA, this work explores how young Somali women artists have been able to critically and creatively shape a more nuanced discourse about their identities. Keywords: Diaspora youth, Black AND Muslim, Somali women, arts-based inquiry, belonging, social media, narrative sharing, resiliency.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.998

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.029
GPT teacher head0.309
Teacher spread0.280 · 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 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
Published2021
Admission routes2
Has abstractyes

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