Pregnant and undocumented: taking work into account as a social determinant of health
Bibliographic record
Abstract
Purpose It is well understood that women’s work situations are critical to their well-being during pregnancy and in terms of potential risks to the fetus. It has also long been known that undocumented women workers face particularly difficult work conditions and being undocumented precludes access to key social benefits (i.e. public health insurance, paid maternity leave, child benefits and subsidized daycare) that support pregnant women and new mothers. Yet, this paper aims to write about the intersection of undocumented women’s pregnancy with work experiences. Design/methodology/approach Drawing on the results of a broader qualitative study that was focussed on access to healthcare for undocumented (and therefore, uninsured) women who were pregnant and gave birth in Montreal, Canada, the authors begin this paper with a review of the relevant literature for this topic related to the work conditions of undocumented women, how work exacerbates barriers to accessing healthcare and the resulting health outcomes, particularly in relation to pregnancy. The authors highlight the social determinants of health human rights framework (Solar and Irwin, 2010), before presenting methodology. In conclusion, the authors discuss how an understanding of undocumented women’s work situations sheds light on their pregnancy experiences. Findings The authors then present participants’ work conditions before becoming pregnant, working conditions while pregnant and employment options and pressures after giving birth. Originality/value The authors emphasize that attention to undocumented pregnant women’s work situations might help health and social service practitioners to better serve their needs at this critical point in a woman’s life and at the beginning of the life of their children, born as full citizens.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".