Barriers to maternal workforce participation and relationship between paid work and health
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Families of children with disabilities experience extra financial strains, and mothers are frequently unable to participate in paid work because of caregiving obligations. METHODS: A mailed survey and follow-up phone calls were used to gather data about mother's health, workforce participation and barriers to inclusion in the workplace (n = 152). Verbatim reports of issues that hindered workforce participation were analysed qualitatively to derive themes. Maternal health-related quality of life (HRQoL) was measured using the Short Form Health Survey Version 2 (SF-36v2). Norm-based conversions were used to compare HRQoL between working and non-working mothers and to compare to population norms. RESULTS: Eighty-two per cent of mothers in the sample wanted and needed to work for pay but indicated over 300 issues that prevent their work participation. Data analysis revealed 26 common issues which prevent work participation. These issues fit into three main categories: mother-related reasons (28%), child-related reasons (29%) and service limitations (43%). Mothers who worked (n = 83) reported significantly better HRQoL than mothers who did not work (n = 69) on five of the eight SF-36v2 dimensions and overall mental health. CONCLUSIONS: Compared to other working Australians, mothers in this study had higher education yet reported poorer health, lower family income and lower workforce participation. Respondents reported that service system limitations were the main barriers to participation in the paid workforce. Investigation of service changes such as increased respite care, availability of outside hours school care, improved professional competency and family-centred services is recommended in order to improve maternal participation in paid work.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it