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Record W3120141271 · doi:10.1177/1757975920984193

Adapting care provision and advocating for unprotected unaccompanied minors in Paris in the context of COVID-19

2021· article· en· W3120141271 on OpenAlexafffund
Lara Gautier, Juan-Diego Poveda, Stéphanie Nguengang Wakap, Magali Bouchon, Amélie Quesnel‐Vallée

Bibliographic record

VenueGlobal Health Promotion · 2021
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsUniversité de MontréalMcGill University
FundersFonds de Recherche du Québec - Santé
KeywordsContext (archaeology)PandemicGuardianHealth carePolitical scienceCivil societyPublic healthPrecarityPopulationCoronavirus disease 2019 (COVID-19)Economic growthMedicineNursingEnvironmental healthLawDiseaseGeographyPolitics

Abstract

fetched live from OpenAlex

Unaccompanied minors (UMs) are children under 18 who arrive on the territory of a foreign country without the care of a guardian. In many countries their access to social and health care services depends on their legal recognition as minors. For instance, in France, high rejection rates of minor status place unprotected UMs in social precarity, such that in Paris, civil society organizations (CSOs) have stepped in to offer social, medical, and psychological care to unprotected UMs. In the context of the COVID-19 pandemic however, CSOs had to adapt their care provision.We review promising CSO-led initiatives to ensure continuity of care for this population. In doing so, we highlight how, by promoting UMs' healthy behaviors in the context of the pandemic, continued social interactions between CSO members and unprotected UMs may have contributed to disease prevention among UMs. In addition, CSOs have continued to advocate for sheltering unprotected UMs, calling on public authorities to take action.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.577
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.058
GPT teacher head0.420
Teacher spread0.362 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations10
Published2021
Admission routes2
Has abstractyes

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