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Record W4391658461 · doi:10.32920/25193690.v1

The Stressors and Challenges of Single Motherhood: The Lived Experiences of African Immigrant Women

2024· preprint· en· W4391658461 on OpenAlexaff
Anna-Lori Stennett-Thomas

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsToronto Metropolitan UniversityHumber Polytechnic
Fundersnot available
KeywordsIntersectionalityImmigrationMental healthStressorGender studiesSociologySettlement (finance)PsychologyPolitical scienceClinical psychology

Abstract

fetched live from OpenAlex

This study examines the settlement experiences of immigrant women of African heritage and more specifically the challenges and stressors of parenting as a single mother. The work and home dynamic expose issues of parental stress, economic instability, increased effects on mental health, and a strained parent-child relationship. To examine this research problem further, I conducted 3 semi-structured interviews with immigrant African women. This study was guided by three theoretical frameworks: transnational feminist theory, intersectionality, and family stress theory. The results of this study highlight the impact of intersectionality on one’s experience of parenting and integration. Additionally, this study brings attention to the lack of focus on single African immigrant women in immigration discourse. The potential benefits of this research include increased visibility of this unseen population, policy implications aimed at improving childcare accessibility, culturally relevant mental health support and reduce the funnelling of racialized immigrant women in precarious work.

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 score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0100.007
Scholarly communication0.0040.003
Open science0.0010.006
Research integrity0.0010.002
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 head0.035
GPT teacher head0.285
Teacher spread0.250 · 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
Published2024
Admission routes1
Has abstractyes

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