Sustaining the Nordic welfare model in the face of population ageing
Bibliographic record
Abstract
the nordic countries are already very ‘aged’ societies, and are set to witness further population ageing in the future. In global comparison, Sweden, Finland and denmark have the 4th, 6th and 11th highest proportions of people aged 60 and over in their populations (united nations 2010: 7). Sweden is currently one of only five countries in the world where people aged 80 and over account for more than 5 per cent of the total population (ibid.: 25). by 2050, the proportion of the population aged 65 and over is predicted to exceed one quarter in Finland, norway and denmark, and to pass the 30 per cent mark in Sweden (united nations 2002). the nordic countries are widely seen as forming a ‘family’ or a ‘regime’ of welfare states that is characterized by extensive redistribution, high legitimacy for public welfare provision, universal (citizenshipbased) and earningsrelated social rights, and comparatively low levels of inequality (kautto 2010). they are also argued to share normative foundations in the form of widespread support for policies that foster equality of opportunities, a high degree of equality of outcomes, and gender equality (kildal and kuhnle 2005). In the area of benefits and services for older people, this translates into pension systems that cover the entire older population at a relatively generous benefit level (kautto 2012), and longterm care systems that grant older adults with disabilities the right to public assistance. Szebehely (2011: 215) states that the hallmark of the nordic ‘service state’ is extensive provision of highquality services that are taken up by all sections of the population, rich and poor alike. What happens when population ageing and extensive welfare state provisions coincide? are these comparatively ‘generous’ welfare states sustainable when confronted with such aged populations and further population ageing? the key word in the question posed above is ‘sustainability’, a concept that can be understood in many ways and that has no single agreed definition in the literature. Sustainable development is generally understood to encompass economic, social and environmental sustainability (see, e.g., Sen 2009). ‘economic sustainability’ usually refers to the sound management of public finances. In the eu, longterm sustainability is assessed by calculating the ‘sustainability gap’. this can be defined as the adjustment required in public finances for covering the debt in the initial year and the aggregate present value of future surpluses and deficits in public finances over the period analysed. the eu also uses another sustainability indicator that reveals the fiscal adjustment needed to meet the Stability and growth Pact’s maximum debt target of 60 per cent of gdP. Spelling out the concept of ‘social sustainability’, kautto (2011) sees basic rights, fairness, intergenerational justice and legitimacy as its component parts. often policy reforms are justified by economic necessities, but if they are carried out in a socially
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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 | 0.017 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.013 |
| Scholarly communication | 0.019 | 0.010 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".