"Put Together": Black Women's Body Stories in Toronto, (Ad)dressing Identity and the Threads That Bind
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.032 | 0.017 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".