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Record W3197506458 · doi:10.18192/uojm.v11is1.6030

Inégalités systémiques et de santé soulignant l’impact disproportionné de la pandémie de COVID-19 sur les peuples autochtones

2021· article· fr· W3197506458 on OpenAlexaffvenueabout
Mahdi Zeghal

Bibliographic record

VenueUniversity of Ottawa Journal of Medicine · 2021
Typearticle
Languagefr
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)Political scienceHumanitiesMedicinePhilosophy

Abstract

fetched live from OpenAlex

Les mesures de santé publique restrictives visant à réduire la propagation d'infection par le COVID-19 ont amené les Canadiens à affronter les perturbations socio-économiques résultant de la pandémie. Cependant, les inégalités systémiques et de santé chez les peuples autochtones les prédisposent à être touchés de manière disproportionnée par la pandémie. Ce groupe minoritaire est confronté à des risques accrus d'infection, de morbidité et de mortalité liés au COVID-19, une détérioration de la santé mentale, une crise économique, ainsi qu'une multitude d'autres problèmes.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.741
Threshold uncertainty score0.516

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.000

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 head0.130
GPT teacher head0.461
Teacher spread0.331 · 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 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

Citations0
Published2021
Admission routes3
Has abstractyes

Explore more

Same venueUniversity of Ottawa Journal of Medicine→Same topicFood Security and Health in Diverse Populations→French-language works237,207→