MétaCan
Menu
← Back to cohort
Record W7005501086

"Put Together": Black Women's Body Stories in Toronto, (Ad)dressing Identity and the Threads That Bind

2018· other· en· W7005501086 on OpenAlexaboutno aff

Bibliographic record

VenueYork University Digital Library (York University) · 2018
Typeother
Languageen
FieldNeuroscience
TopicNeurology and Historical Studies
Canadian institutionsnot available
Fundersnot available
KeywordsScholarshipIdentity (music)IntersectionalityWhite (mutation)AutoethnographyFeminismMasculinitySocial constructionismThe SymbolicWomen of color
DOInot available

Abstract

fetched live from OpenAlex

Put Together: Black Womens Body Stories in Toronto, (Ad)dressing Identity & The Threads That Bind centers child and adult body stories shared by eight Black women, including the author, 29 to 39 years of age living in Toronto one of the most diverse cities in the world. Historically, the lived experiences and body talk of Black women and girls have been routinely marginalized and tangentially documented within dominant monochromatic body image literature which usually centers the experience of white women and girls. The geography of the seven participants is intentional as it further destabilizes the Americentric lens of fat studies and Black feminist scholarship by adding to the canon the stories of Toronto-based women who self-identify with both blackness and fatness : two embodiments often misperceived, misrepresented and constructed as excess(ive) in need of repair and regulation. Through a hybrid, intersectional framework, informed by tenets of fat studies, anti-racist, Black feminist thought, symbolic interactionism and sartorial scholarship this dissertation intends to demonstrate the socially constructed educational societal curriculum the everyday and systemic good body, bad body lessons - learned through social interactions with significant and generalized others and through the symbolic and cultural currency of objects such as clothing and self-fashioning practices that help to shape how these participants think, feel and remember their bodies through the qualitative, unstructured interview. Their stories are thematically analyzed and the threads that bind and bound them are made apparent. \nParticipants accommodation and resistance of normalized body ideals and social forces are explored. Particular attention is paid to their material self-representation as impression management through dress since respectability politics and appearance factor significantly in their body stories along with various activisms that help them buck the system through self-definition and valuation. Participants raced, gendered, and sized body stories are shaped through their family, schooling, workplace, public space, intimate relationships, community activism and sartorial engagements among other key influencers and as Put Together unfolds, their experiences with racism, sexism, class bias, fat phobia and other intersectional forms of body-based discrimination, harassment and gender-based violence, and the mental health implications of these embodied traumas are laid bare. \nTraditionally, it is postulated that Black women have little worries about their weight, their bodies and are more welcoming of fatness. However, Put Together demonstrates the falsehood of this essentializing assumption and addresses the paucity in the research. The double whammy of fatness and Blackness and the accompanying stereotypes set up a scenario where the Black women in this research are arguably engaged in a heightened awareness a triple consciousness of size, gender and race corporeality. This qualitative research can support educators, activists and policy pertaining to appearance-based discrimination, equity and inclusivity. It also supports the need for more inclusive sizing, good quality and affordably-priced clothing options for fat bodies. Body-based bullying, size discrimination and anti-Black racism are inextricably linked in this study. The outcome of that to future studies can be more comprehensive, culturally-relevant and size diverse research, images, analyses and conversations on body image which includes race and representation, in school curriculum, in workplace human rights, heath and wellness and in fashion industry policies and practice for instance.

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)0.003
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: Other · Consensus signal: none
Teacher disagreement score0.359
Threshold uncertainty score0.722

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0320.017
Scholarly communication0.0060.003
Open science0.0020.008
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0050.001

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 head0.020
GPT teacher head0.199
Teacher spread0.179 · 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
GenreOther

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

Explore more

Same venueYork University Digital Library (York University)→Same topicNeurology and Historical Studies→French-language works237,207→