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Record W2010467813 · doi:10.1080/09581590802376234

Health as a resource for everyday life: advancing the conceptualization

2009· article· en· W2010467813 on OpenAlexafffundabout
Deanna L. Williamson, Jeff Carr

Bibliographic record

VenueCritical Public Health · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsEmployment and Social Development CanadaUniversity of Alberta
FundersHealth Canada
KeywordsConceptualizationHealth policyHealth promotionPublic healthPublic economicsGoods and servicesHealth equityPublic relationsSociologyBusinessEconomicsHealth careEconomic growthMedicinePolitical scienceNursing

Abstract

fetched live from OpenAlex

This paper examines the conceptualization of health as a resource and the implications that such a definition has for public health programs and policies. First introduced in the Ottawa Charter for Health Promotion, health is commonly defined by practitioners, policy makers, and scholars as a resource for everyday life. However, despite frequent references to health as a resource, little attention has been paid to the meaning of this one-line phrase. Thus, we draw on a multidisciplinary body of literature to examine key features of health that characterize it as a resource, as well as its similarities, differences, and associations with other resources. We argue that, as a resource, health is appropriately conceptualized as a type of capital that can be invested in by individuals and societal institutions to achieve positive health returns. Similar to human capital, health is embodied in individuals, and, as such, it is not a tradable resource like money. Health cannot be exchanged or sold for goods and services and it cannot be obtained directly in exchange for goods and services. Instead, as a type of capital, health is a stock of biopsychosocial resources that people can draw on to participate in society. Although health shares some characteristics with human capital, we contend that health is not a component of human capital, as some scholars indicate. Lastly, we maintain that there are important program and policy implications, both positive and negative, of adopting an economic definition of 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)0.007
metaresearch head score (Gemma)0.006
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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.004
Science and technology studies0.0030.051
Scholarly communication0.0080.015
Open science0.0020.007
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0030.000

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 head0.083
GPT teacher head0.453
Teacher spread0.370 · 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

Citations58
Published2009
Admission routes3
Has abstractyes

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