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Record W2130397431 · doi:10.1177/1403494813506522

Challenges to promoting health in the modern welfare state: The case of the Nordic nations

2013· article· en· W2130397431 on OpenAlexaff
Dennis Raphael

Bibliographic record

VenueScandinavian Journal of Public Health · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsYork University
Fundersnot available
KeywordsWelfare statePublic healthWelfarePovertyHealth promotionPolitical scienceGlobalizationEconomic growthImmigrationHealth policyWelfare capitalismEquity (law)Development economicsEconomicsHealth careMedicinePolitics

Abstract

fetched live from OpenAlex

AIMS: Finland, Norway, and Sweden are leaders in promoting health through public policy action. Much of this has to do with the close correspondence between key health promotion concepts and elements of the Nordic welfare state that promote equity through universalist strategies and programs that provide citizens with economic and social security. The purpose of this article is to identify the threats to the Nordic welfare states related to immigration, economic globalization, and welfare state fatigue. METHODS: Through a critical analysis of relevant literature and data this article provides evidence of the state of the Nordic welfare state and some of these challenges to the Nordic welfare state and its health promotion efforts. RESULTS: There is evidence of declining support for the unconditional Nordic welfare state, increases in income inequality and poverty, and a weakening of the programs and supports that have associated with the excellent health profile of the Nordic nations. This is especially the case for Sweden. CONCLUSIONS: It is argued that the Nordic welfare states' accomplishments must be celebrated and used as a basis for maintaining the public policies shown to be successful in promoting the health of its citizens.

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)0.014
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.774
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.094
GPT teacher head0.384
Teacher spread0.290 · 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 teacher head, not a consensus.

Study designQualitative
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

Citations61
Published2013
Admission routes1
Has abstractyes

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