MétaCan
Menu
Back to cohort
Record W7132936252

A Culturally Relevant "NoBody's Perfect" Parenting Program for African Immigrant Women in Canada

2021· dissertation· W7132936252 on OpenAlexaboutno aff
Annette Atugonza Bazira-Okafor

Bibliographic record

VenueTSpace · 2021
Typedissertation
Language
FieldSocial Sciences
TopicRacial and Ethnic Identity Research
Canadian institutionsnot available
Fundersnot available
KeywordsImmigrationAgency (philosophy)IndigenousColonialismProsperityCurriculumPoliticsChild rearing
DOInot available

Abstract

fetched live from OpenAlex

This study examines the curriculum and impact of The Nobody’s Perfect parenting program delivered by the Public Health Agency of Canada. Specifically, the study challenges notions of this program as an adaptable and effective model for training first time, young and immigrant mothers in parenting skills that empower both families and children. The present study highlights the program’s deeply Eurocentric and Western values and imaginations through the case of 17 African immigrant mothers whose voices and knowledge are erased and devalued by such modern Canadian parenting training schemes presuming these racialized women’s cultures backward and their childrearing experiences unusable in the Canadian context. Drawing from 17 personal interviews with immigrant women from 12 countries in Africa, the study illuminates the complex nature of the childrearing experiences of these women, shining light especially on their transnational and hybridized parenting practises informed by African and indigenous cultural values and beliefs yet already internalized parental models disseminated by European colonialism and political domination over Africa. The analysis leads to recommendations for ways to ground parental support in Canada in immigrant cultures thus positioning immigrant children and families for prosperity and wellbeing in Canada.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.226

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0150.002
Scholarly communication0.0010.000
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.038
GPT teacher head0.413
Teacher spread0.375 · 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 designObservational
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 routes1
Has abstractyes

Explore more

Same venueTSpaceSame topicRacial and Ethnic Identity ResearchFrench-language works237,207