5.A. Round table: Public Health Economics at the heart of Well-being Economics
Bibliographic record
Abstract
Abstract The transition from an economy centred on economic growth to one centred on well-being makes public health central to political and economic priorities. However, public health economics is rarely used as a concept and as a central part of welfare economics debates. This round table will critically reflect on the role of public health economics as a transformer of public policy and economic evaluation. The main objective is to understand and discuss how current public health economics tools can be adapted and extended to guarantee public policies that promote well-being throughout the life cycle, but also equity and sustainability. The panel will be divided into three thematic sections: 1. Definitions of concepts - The definitions and relationship between public health economics and wellbeing economics will be debated through approaches based on capacities, health equity and prevention. The risk of conceptual dilution (‘wellbeing-washing’) will also be analysed. 2. Methodological Steps - The current suitability of economic evaluation tools for wellbeing outcomes will also be discussed, as well as new approaches such as distributive cost-effectiveness analysis (DCEA) and the use of WELLBYs, as alternatives for capturing social values. 3. Transfer to Policies - The role of public health economics in the preparation and evaluation of public policies beyond the health sector will be debated, through ‘Health for All Policies’, well-being budgets and economic evaluation in sectors such as housing, mobility and the environment. The panel will include perspectives from different geographical areas, types of organisations and levels of response, fostering a diversity of scientific and institutional perspectives, but will also include contributions and debate with the audience, focusing on practical examples and future directions. This session was supported by National Funds through FCT - Fundação para a Ciência e a Tecnologia,I.P., within CINTESIS, R&D Unit (reference UIDB/4255/2020). Key messages • Public health economics is essential for guiding public policies centred on well-being in a practical and methodologically consistent way. • New approaches must be considered, including social values beyond the market. Speakers/Panellists Michele Cecchini OECD, Paris, France Filipa Sampaio Uppsala University, Uppsala, Sweden Shehzad Ali Department of Epidemiology and Biostatistics, Western University, London, Canada Karl Emmert-Fees Technical University of Munich, Munich, Germany
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.013 | 0.017 |
| Insufficient payload (model declined to judge) | 0.097 | 0.034 |
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".