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Record W2583678187 · doi:10.1080/07399332.2017.1290099

“You feel you have to be made of steel”: The strong Black woman, health, and well-being in Nova Scotia

2017· article· en· W2583678187 on OpenAlexafffundabout
Josephine Etowa, Brenda L. Beagan, Felicia Eghan, Wanda Thomas Bernard

Bibliographic record

VenueHealth Care For Women International · 2017
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsMount Saint Vincent UniversityDalhousie UniversityUniversity of Ottawa
FundersNova Scotia Health Research Foundation
KeywordsPrideNova scotiaConstruct (python library)Visitor patternQualitative researchRacismPerceptionPsychologyGender studiesIconTollSocial psychologySociologyMedicinePolitical science

Abstract

fetched live from OpenAlex

The "strong Black woman" construct has been well-documented in the United States as both an aspirational icon and a constricting burden for African-heritage women. It has not been examined among African-Canadians. Drawing on qualitative interviews and standardized measures with 50 African-heritage women in Eastern Canada, our analysis reveals their perceptions of the construct as both strongly endorsed as a source of cultural pride, yet also acknowledged to take a terrible toll on health and well-being. The construct arises from and directly benefits racism. It is imperative that health professionals understand the ways it shapes health and help-seeking behaviors.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.110
Threshold uncertainty score0.222

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0120.006
Scholarly communication0.0030.001
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.063
GPT teacher head0.436
Teacher spread0.373 · 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

Citations56
Published2017
Admission routes3
Has abstractyes

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