Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".