Documenting the undocumented - The use of maternity care and perinatal outcomes among undocumented migrants in Norway
Bibliographic record
Abstract
Irregular legal status is a recognized risk factor for limited access to health care services, preterm birth and low birth weight. However, pregnant undocumented migrants are rarely included in population surveys. This thesis aims to explore the use of maternity care services by undocumented pregnant migrants in Norway and to investigate the association between legal status and severity of pregnancy-related conditions at presentation, and between legal status and perinatal health outcomes.\nThe population of interest were pregnant undocumented migrants aged 18-49 years living in Norway from 1999-2020. This thesis is based on collected data from medical records from non-governmental (NGO) clinics in Bergen and Oslo serving undocumented migrants and their referral hospitals from 2009-2020, medical records from the Oslo Accident and Emergency Outpatient Clinic (OAEOC) from 2009-2019, and registry data from the Medical Birth Registry of Norway (MBRN) from 1999-2020.\nIn total, we found 5856 undocumented migrant women giving birth from 1999-2020 representing 0.5% of all births in Norway. Undocumented migrants had six times higher risk of perinatal death in the offspring compared with non-migrants and four times higher risk compared with documented migrants. In addition, undocumented migrant women had 54% higher risk of giving preterm birth compared with non-migrants and 47% higher risk compared with documented migrants. About half of the women came to the NGO clinics for antenatal care after their first trimester and a quarter came after gestational week 22. Pregnant undocumented migrants presenting at the OAEOC had an 86% increased risk of being triaged with a high level of urgency at presentation and a 68% increased risk of being hospitalized compared with pregnant residents (migrants and non-migrants).\nBased on the data, we found delayed, substandard antenatal care and an increased risk of adverse perinatal outcomes among pregnant undocumented migrants. Neither maternal origin nor maternal gestational health conditions could explain the differences in perinatal mortality, which indicates that access to health care services may still play a role, even after the 2011 legal reform, which aimed at improving access to health services for this group.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".