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Record W4231446026 · doi:10.32920/ryerson.14662098

Growing up with black hair in the GTA: three women share their stories

2021· preprint· en· W4231446026 on OpenAlexaffabout
Melissa Bagirakandi

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicGender Roles and Identity Studies
Canadian institutionsEducation and Early Childhood Development
Fundersnot available
KeywordsBlack hairBlack womenIdentity (music)Context (archaeology)Black africanPsychologyGender studiesArtSociologyHistoryAestheticsGenealogy

Abstract

fetched live from OpenAlex

The literature demonstrates that Black hair affects the identity of Black women. However, there is little research on how Black hair affects the identity of Canadian Black girls. For the purpose of this study, Black hair will refer to coiled textured hair, often referred to as “kinky”. The goal of the present study was to understand the effects of Black hair on the identity of Black girls between the ages of 5 and 12. Three Black women between the ages of 20 and 35 were asked to recall their experiences growing up in Canada with Black hair. Following a Black feminist approach, data was collected through story telling in an open-ended interview and four themes were identified : caring for Black hair, hair altering, the future of Black hair, and influences on Black hair styling. The women in the study have a hopeful vision for the future of Black hair. Keywords: Black hair, identity, Canadian context, childhood

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)0.003
metaresearch head score (Gemma)0.006
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 score0.197
Threshold uncertainty score0.396

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0460.020
Scholarly communication0.0080.004
Open science0.0030.007
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0040.000

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 head0.060
GPT teacher head0.294
Teacher spread0.234 · 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
Published2021
Admission routes2
Has abstractyes

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