Os regimes de Welfare de Esping-Andersen e sua demonstração no cotidiano de EUA, Canadá, França, Inglaterra, Cuba e Irlanda - Uma análise de Sicko e Inside I'm dancing: Esping-Andersen's Welfare regimes and their demonstration in the daily lives of the USA, Canada, France, England, Cuba and Ireland - An analysis by Sicko and Inside I'm dancing
Bibliographic record
Abstract
O objetivo deste artigo e apresentar as caracteristicas de atendimento de varias redes de protecao social em diversos paises (Canada, Reino Unido, Franca, Cuba, Irlanda e EUA) bem como urn comparativo, corn foco principal na atencao a satide e no bem-estar social que tais redes proporcionam. Tal analise e feita a partir de duas obras cinematograficas: um documentario e urn drama. 0 documentario trata-se do polemic° SOS Saude de Michael Moore, obra focada na critica de os EUA serem o imico pais do ocidente a Waco possuir um sistema de saúde universal. 0Odrama, por sua vez, trata-se do filme "Os melhores dias de nossas vidas" de Damien O'Donnel, que conta a historia de dois deficientes fisicos irlandeses e as dificuldades que enfrentam em seu dia-a-dia. A partir dos detalhes apresentados nestas obras e atraves de pesquisa a literatura sobre Estado de Bem-Estar Social faz-se entao uma exposicao destes modelos, bem como uma analise comparativa.
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 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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.020 | 0.020 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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; 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".