Health and social needs of unprotected unaccompanied minors in Paris in the context of COVID-19
Bibliographic record
Abstract
Abstract Background Unaccompanied minors (UMs) are children under 18 settling in foreign countries without the care of a guardian. Host countries' governments are responsible for the care of UMs. In France, UMs theoretically receive child protection. However, assessment systems frequently deny their protection because of minority status rejection. As a result, they navigate through social precarity and have limited access to healthcare services. In Paris, the non-governmental organisation Médecins du Monde (MdM) offers them medico-psycho-social care. In March 2020, lockdown measures to contain COVID-19 further reduced unprotected UMs' access to social and healthcare services. This critical situation prompted MdM to adapt their care provision to the pandemic. In this research, we sought answers to the following research question: what were unprotected UMs' social and healthcare needs during lockdown and what was MdM's response? Methods First, we estimate the evolution of social and healthcare needs of a cohort of 58 unprotected UMs during the eight-week lockdown using secondary data. Second, using interview data with MdM volunteers and staff (n = 15) we further explore UMs' needs and document the experience of phone consultations with this cohort of UMs. Preliminary Results Time series show a constant increase of UMs' needs through time. MdM's new form of care provision may have contributed to alleviate their feeling of isolation. It also had unintended consequences. Conclusions In light of the alarming healthcare status of unprotected UMs, we recommend that France implements the public health authorities' recommendation to provide appropriate shelter to UMs regardless of their status, at least during health crises. Key messages This study fills a research gap related to a pressing political and public health issue. This study advances evidence-informed debates debates on the influence of models of care provision on UMs’ social and healthcare needs during health crises.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".