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Record W2181728390 · doi:10.1093/pch/15.4.199

The health of Canada's children. Part IV: Toward the future

2010· article· en· W2181728390 on OpenAlexaffabout
Dennis Raphael

Bibliographic record

VenuePaediatrics & Child Health · 2010
Typearticle
Languageen
FieldHealth Professions
TopicChild and Adolescent Health
Canadian institutionsYork University
Fundersnot available
KeywordsDisadvantagedPublic healthHealth policyAction (physics)Health carePolitical sciencePublic relationsPublic policySocial determinants of healthEconomic growthMedicineNursingEconomics

Abstract

fetched live from OpenAlex

Canadian children's health is influenced, in large part, by the living circumstances that they experience. These living circumstances - also known as the social determinants of health - are shaped by public policy decisions made by governmental authorities. While public policy should be focused on providing all Canadian children with the living circumstances necessary for health, it appears that Canada is far from achieving this goal. Instead, there are programs directed at Canada's most severely disadvantaged families and children. While vital, these programs appear to achieve less than that which would be achieved if governmental action was designed to strengthen the social determinants of health for all children. Considering the governmental actions that would achieve this goal are well known - with rather little evidence of policy implementation - it is essential to understand the processes by which public policy is made. An important physician role - in addition to providing responsive health care services - is to become forceful advocates for public policy in the service of health. It is in the latter sphere that physician involvement may yield the strongest benefits for promoting children's health.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.076
Threshold uncertainty score0.551

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0080.003
Scholarly communication0.0040.001
Open science0.0020.002
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0110.001

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.

Opus teacher head0.014
GPT teacher head0.314
Teacher spread0.300 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations3
Published2010
Admission routes2
Has abstractyes

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