MétaCan
Menu
Back to cohort
Record W3096668970 · doi:10.5539/gjhs.v12n12p130

Highly Skilled South Asian Migrant Women in Australia: Hidden Economic Assets

2020· article· en· W3096668970 on OpenAlexvenueno aff
Najia Syed, Cathy Banwell, Tehzeeb Zulfiqar

Bibliographic record

VenueGlobal Journal of Health Science · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsDeskillingWork (physics)Financial independenceIndependence (probability theory)Work–life balanceBalance (ability)Qualitative researchEconomic growthFamily lifeBusinessPolitical scienceDemographic economicsSocioeconomicsSociologyPsychologyEconomics

Abstract

fetched live from OpenAlex

Finding a balance between work and family life is challenging for many women, particularly migrant women living in Australia without family support. This study provides insights into their dilemmas, difficulties and strengths in terms of household responsibilities and employment pressures. Design: Qualitative, in-depth interviews were conducted with ten South Asian skilled mothers living in Canberra, Australia. Findings: Participants were positive about contributing to their family’s income and gaining financial independence. However, as skilled migrant women, they struggled to use their work skills due to increased demands of domestic responsibilities. They often negotiated work and family life by seeking low-prospect careers. Conclusion: The socio-cultural factors faced by South Asian migrant women have a significant impact on their work-life balance. Deskilling, increased work pressures and lack of support may negatively impact their career aspirations and well-being. Flexible policies can help mitigate these barriers to help migrant women maintain a work-life balance.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.808

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.042
GPT teacher head0.352
Teacher spread0.310 · 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 teacher head, 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

Citations2
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueGlobal Journal of Health ScienceSame topicWork-Family Balance ChallengesFrench-language works237,207