Healthcare access for migrant children in England during the COVID-19 pandemic
Bibliographic record
Abstract
Access to healthcare services without discrimination is fundamental to the right to health. The principles of equitable, accessible, affordable healthcare are also embedded within the United Nations (UN) resolution on Universal Health Coverage, hailed as ‘the single most powerful concept that public health has to offer’ by the former WHO director-general.1 In 2016, the UN Committee on the Rights of the Child raised significant concerns regarding healthcare access inequalities between migrant and non-migrant children in the UK.2 These unresolved concerns and subsequent serious child health consequences have been echoed repeatedly by leading health and migrant support experts.3 The global COVID-19 pandemic and impacts of mitigation policies have dealt multiple blows to the health and well-being of many sectors of the population, particularly those already living precarious lives. Migrant families and children are recognised as a group already burdened with health challenges and barriers to healthcare access which risk further exacerbation during and beyond the COVID-19 pandemic.3 The ongoing public health crisis presents an urgent and distinctive opportunity to permanently address the unacceptable hostile policy and practice environment that restricts equitable healthcare access, endangers child health and so poorly enables the rights of migrant children to be realised. In 2017, an estimated 6 208 000 foreign national individuals resided in the UK, including 332 604 children and young people (CYP) from the European Economic Area (EEA+) and 332 000 undocumented CYP. An estimated 133 000 CYP without secure immigration status were estimated to be living in London alone.4 Undetected victims of international human trafficking, including family units and children, are likely to number in their thousands.5 In 2018, asylum seekers represented approximately 6% of immigrants (34 500 people) in the UK.6 Five thousand six hundred and fifty-five dependent children under the age of 18 years were included in asylum …
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".