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Health, Wellness and Wellbeing

2019· article· en· W2954816282 on OpenAlexvenueno aff
Max Holdsworth

Bibliographic record

VenueInterventions économiques · 2019
Typearticle
Languageen
FieldPsychology
TopicPsychological Well-being and Life Satisfaction
Canadian institutionsnot available
Fundersnot available
KeywordsHealth promotionLegislationHealth careHappinessHealth policySocial determinants of healthPublic relationsPolitical scienceHRHISHealth equityHealth lawInternational healthEconomic growthPsychologyLawEconomics

Abstract

fetched live from OpenAlex

A population’s health is contributed to by many factors outside of the clinical setting. American literature and research are asserting the Social Determinants of Health, while terms like wellness and wellbeing are also important. The discourse between wellness and wellbeing show they are both components of health, but wellbeing relates to subjective happiness. The United States health care system spends a lot of money, compared to other countries, showing a skewed allocation of resources. As the United States recognizes a broader definition of health to include wellness and wellbeing, national health promotion and legislation represent this. Policies concerning wellness and health prevention are of particular importance in legislation of the Patient Protection and Affordable Care Act of 2010, for example. The focus of American health policy cannot, however, turn away from the more fundamental problem that there are many Americans without health insurance who are unable to get or pay for the clinical care they need. In moving policy forward, more quantitative information and political dedication would help wellness and wellbeing along with health care come onto the health policy agenda.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.651
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.043
GPT teacher head0.364
Teacher spread0.322 · 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; both teacher heads agree on what is shown here.

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

Citations22
Published2019
Admission routes1
Has abstractyes

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