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Record W2604334506 · doi:10.1177/1403494817698889

New hypotheses regarding the Danish health puzzle

2017· review· en· W2604334506 on OpenAlexaff
May Bakah, Dennis Raphael

Bibliographic record

VenueScandinavian Journal of Public Health · 2017
Typereview
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsYork University
Fundersnot available
KeywordsLife expectancyUnemploymentSocial securityJob securityWelfare stateDanishDemographic economicsWelfarePublic healthInequalityPopulationEconomicsPopulation ageingDevelopment economicsEconomic growthPolitical scienceSociologyDemographyMedicineWork (physics)

Abstract

fetched live from OpenAlex

AIMS: Nordic welfare states have achieved admirable population health profiles as a result of public policies that provide economic and social security across the life course. Denmark has been an exception to this rule, as its life expectancies and infant mortality rates since the mid-1970s have lagged behind the other Nordic nations and, in the case of life expectancy, behind most Organisation for Economic Co-operation and Development nations. METHODS: In this review paper, we identify a number of new hypotheses for why this may be the case. RESULTS: These hypotheses concern the health effects of neo-liberal restructuring of the economy and its institutions, the institution of flexi-security in Denmark's labour market and the influence of Denmark's tobacco and alcohol industries. Also of note is that Denmark experienced higher unemployment rates during its initial period of health stagnation, as well as its treatment of non-Western immigrants and high wealth inequality and, until recently, the fact that Denmark did not systematically address the issue of health inequalities. CONCLUSIONS: These hypotheses may serve as covering explanations for the usually provided accounts of elevated behavioural risks and psychosocial stress as being responsible for Denmark's health profile.

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)0.018
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.708
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0180.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0010.000
Science and technology studies0.0080.000
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.004
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 head0.554
GPT teacher head0.555
Teacher spread0.001 · 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 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

Citations8
Published2017
Admission routes1
Has abstractyes

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