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Record W136461797

How We See Ourselves : The Beauty Makeup of the Black Canadian Woman

2010· dissertation· en· W136461797 on OpenAlexaboutno aff
Susan-Blanche Chato

Bibliographic record

VenueSpectrum Research Repository (Concordia University) · 2010
Typedissertation
Languageen
FieldArts and Humanities
TopicArchitecture, Design, and Social History
Canadian institutionsnot available
Fundersnot available
KeywordsBeautyAestheticsArtArt historyHistory
DOInot available

Abstract

fetched live from OpenAlex

How We See Ourselves: The Beauty Makeup of the Black Canadian Woman Susan-Blanche Chato The concept of beauty is a prime value in North American culture yet the feminine beauty ideal has conventionally been associated with the White population, causing a dichotomy of norms between Whites and non-Whites.This thesis reviews the historical and contextual nature of beauty amongst women of African descent and the Diaspora in the works of Patricia Hill Collins, bell hooks, Malcolm X, W.E.B DuBois and many others on such topics as skin color, hair texture, health, body image and racism.To determine the continuing salience of these issues in the lives of Black women, I interviewed and surveyed ten second generation African (Black) Canadians.The were integral to this project.First, I would like to thank God for placing me on this journey and for teaching me a new meaning of strength, perseverance and focus.I would also like to express my gratitude to my thesis committee.An immense thanks to Dr. Anthony Synnott whose resourcefulness, patience and guidance illuminated the many dimensions of this project.His encouragement and experience throughout the research process was invaluable.Special thanks to Professor Brenda Rowe and Dr. Meir Amor for their insightful suggestions, unwavering support and constructive dialogue.I am deeply grateful to all the respondents for sharing their thoughts and stories.Their voices were the motivating force in completing this project and they have enlightened me to the new possibilities linked to this subject matter more than they will ever know.A special thanks to my father, Dr. Martin Chato for his patience editing the drafts and his sound input.Also, thanks extend to Dr. Roger MacLean for his foresight, optimism and reassurance over the course of this project.My heartfelt appreciation and love goes out to those whose support and compassion over this period of time was a blessing.They prayed and -stood in the gap‖ throughout the process and were part of my inspiration, in particular my mother Victoria, Aunty

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.070
Threshold uncertainty score0.331

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0700.019
Scholarly communication0.0050.002
Open science0.0020.004
Research integrity0.0030.007
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 head0.028
GPT teacher head0.234
Teacher spread0.206 · 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
Published2010
Admission routes1
Has abstractyes

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