Para a melhoria dos serviços sociais a idosos pobres em Portugal / improving social services for the elderly poor in Portugal
Bibliographic record
Abstract
A literatura cientifica sobre o envelhecimento centra-se predominantemente sobre o aumento da populacao idosa na estrutura demografica dos paises e sobre o impacto dessas transformacoes na sustentabilidade do sistema de proteccao social e de saude, parecendo desprezar os estudos sobre a pobreza. Este artigo pretende relacionar o envelhecimento com a pobreza em idosos e com os servicos sociais, tendo presente a estrategia europeia de luta contra a pobreza e a sua transposicao para o quadro normativo nacional. Nesta linha de analise destacamos a configuracao dos servicos sociais em Portugal, tendo em conta o nivel central, regional e local, ponderando a sua relevância para a proteccao e inclusao social das pessoas idosas. Nestes ultimos anos, os servicos sociais de apoio as camadas desfavorecidas da populacao, sobretudo no caso dos idosos pobres, tem merecido uma atencao particular. Contudo, em muitos paises ocidentais, a recente crise economica e financeira tem levado os estados a retrairem o investimento, pondo em causa a qualidade dos servicos sociais. Terminamos com uma reflexao sobre o modo como as politicas publica pode responder a uma populacao cada vez mais dependente dos recursos formais e chamamos a atencao para a necessidade de mais estudos empiricos sobre este tema. Scientific literature on ageing focuses predominantly in the demographic structure of the countries and the impact of these changes in the sustainability of social protection and health, ignoring poverty studies. This article aims at relating elder aging and poverty with social services taking into account the European strategy to combat poverty and its transposition into the national legal framework. In this line of analysis we highlight the configuration of social services in Portugal, given the central, regional and local levels, considering its relevance to the protection and social inclusion of the elderly. In recent years social services to support disadvantaged populations, particularly the elderly poor, have received particular attention. However, in many Western countries the recent economic and financial crisis has led states to hold back on investment, jeopardizing the quality of social services. We end with a reflection on how public policy can respond to a population increasingly dependent on formal resources and call attention to the need for more empirical studies on this topic. Palavras-chave/ Key-words Envelhecimento; pobreza; politicas publicam; servicos sociais. Ageing, poverty, public policy, social services
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.009 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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; both teacher heads agree on what is shown here.
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".