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Record W4403559203 · doi:10.1093/pch/pxae071

Health insurance for all children in Quebec? Ethical reflections on the implementation of PL 83

2024· article· en· W4403559203 on OpenAlexafffundabout
Annie Liv, Patricia Li, Ryoa Chung, Samir Shaheen-Hussain, Saleem Razack, Joanne Liu, Nathalie Gaucher

Bibliographic record

VenuePaediatrics & Child Health · 2024
Typearticle
Languageen
FieldHealth Professions
TopicChild and Adolescent Health
Canadian institutionsCentre Hospitalier Universitaire Sainte-JustineUniversity of British ColumbiaMcGill UniversityMcGill University Health CentreUniversité de Montréal
FundersCentre hospitalier universitaire Sainte-JustineRoyal College of Physicians and Surgeons of Canada
KeywordsHealth insuranceBusinessEnvironmental healthPsychologyPolitical scienceMedicineHealth careLaw

Abstract

fetched live from OpenAlex

The adoption of Projet de loi 83 (PL83) in 2021 aimed to grant previously uninsured migrant children in Quebec access to provincial public health insurance. Three years later, health professionals continue to encounter children who should be eligible for provincial insurance through PL83 but remain uninsured and who face various structural barriers that contribute to this limited access (language, administrative navigation, and access to information). This commentary, based on the conceptual framework of the ethics of care, considers autonomy as the ability to make one's own choices with support from others. Contrary to a conception of autonomy as self-sufficiency, the ethics of care encourages the design of policies and implementation measures capable of helping vulnerable individuals overcome barriers. In the case of access to healthcare for migrant children, we suggest presumptive eligibility and raising awareness among all key stakeholders who interact with parents, from admission and administrative staff to physicians.

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 imitation

Not 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.

metaresearch head score (Codex)0.028
metaresearch head score (Gemma)0.030
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.900
Threshold uncertainty score0.724

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0280.030
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0270.022
Scholarly communication0.0080.003
Open science0.0050.005
Research integrity0.0220.023
Insufficient payload (model declined to judge)0.0020.000

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 head0.063
GPT teacher head0.471
Teacher spread0.409 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations0
Published2024
Admission routes3
Has abstractyes

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