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Record W2186344737

Social Determinants of Health: A Quick Guide for Health Professionals 1

2013· article· en· W2186344737 on OpenAlexaboutno aff
Juha Mikkonen, Dennis Raphael

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsHealth promotionAgency (philosophy)Public healthGovernment (linguistics)Social determinants of healthOfficerCommunity healthHealth policyInternational healthHealth educationPublic relationsPolitical scienceEconomic growthBusinessMedicineSociologyNursingLawEconomicsSocial science
DOInot available

Abstract

fetched live from OpenAlex

The primary factors that shape the health of Canadians are not medical treatments or lifestyle choices but rather the living conditions they experience. These conditions have come to be known as the social determinants of health (SDH).[1] The importance to health of living conditions was first established in the mid-1800s[2,3] and has been enshrined in Canadian government policy documents since the mid-1970s.[4] In fact, Canadian contributions to the SDH concept have been so extensive as to make Canada a “health promotion powerhouse” in the eyes of the international health community.[5] Recent reports from Canada’s Chief Public Health Officer,[6] the Canadian Senate[7], and the Public Health Agency of Canada[8] continue to document the importance of the SDH. But this information – based on decades of research and hundreds of studies in Canada and elsewhere – tells a story that is still unfamiliar to most Canadians. Canadians are largely unaware that our health is shaped by how income and wealth are distributed, whether or not we are employed, and if so, the working conditions we experience. Furthermore, our well-being is determined by the health and social services we receive, along with our access to quality education, food and housing, and other factors.[9] Contrary to the assumption that Canadians have personal control over these factors, in most cases these living conditions are – for better or worse – imposed upon us by the quality of the communities, housing situations, work settings, health and social service agencies, and educational institutions we have access to .[10] There is much evidence that the quality of the SDH Canadians experience helps explain the wide health inequalities that exist. How long Canadians can expect to live and whether they experience cardiovascular disease or adult-onset diabetes is very much determined by their living conditions.[11,12] The same goes for the health of their children: differences among Canadian children in surviving beyond their first year of life, in experiencing afflictions such as asthma and injuries, and whether they fall behind in school, are strongly related to the SDH they are exposed to.[13] Research is also finding that the quality of these health-shaping living conditions is strongly determined by decisions that governments make in a range of different public policy domains.[14] Governments at the municipal, provincial/territorial, and federal levels create policies, laws and regulations that influence how much income Canadians receive through employment, family benefits or social assistance, along with the quality and availability of affordable housing, the kinds of health and social services and recreational opportunities we can access, and even what happens when Canadians lose their jobs during economic downturns. These experiences also provide the best explanations for how Canada compares to other nations in overall health. Canadians generally enjoy better health than Americans, but do not do

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)0.008
metaresearch head score (Gemma)0.024
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: Other · Consensus signal: none
Teacher disagreement score0.128
Threshold uncertainty score0.429

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.024
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0130.012
Science and technology studies0.0020.002
Scholarly communication0.0050.007
Open science0.0050.005
Research integrity0.0050.009
Insufficient payload (model declined to judge)0.1280.048

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 head0.115
GPT teacher head0.504
Teacher spread0.388 · 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
GenreOther

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

Citations1
Published2013
Admission routes1
Has abstractyes

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