Five cities, from Athens to Montevideo, are recognised for public health work
Bibliographic record
Abstract
Five cities, from Athens to Montevideo, are recognised for public health work Elisabeth MahaseFive cities across the globe have been awarded $150 000 at the first Partnership for Healthy Cities Summit, to continue their work in preventing noncommunicable diseases (NCDs) and injuries.The summit, which took place in London on 15 March, saw global health leaders and mayors from more than 50 major cities come together to discuss urgent public health concerns and best practices that save lives and create healthier cities.The winning cities included Athens, Greece, for increasing access to naloxone for opioid overdoses; Bengaluru, India, for reducing smoking in public places; and Vancouver, Canada, for launching an online public health data tool that tracks population health indicators, as well as working with urban indigenous communities to inform data management.Other cities recognised were Mexico City, where the introduction of a bike path on a busy road led to a 275% increase in cyclists, and Montevideo, Uruguay, which has established nutritional standards for the preparation and sale of food in government agency offices and some public universities.The Partnership for Healthy Cities was founded in 2017 and is made up of 70 cities around the world who work together to prevent NCDs and injuries, which are responsible for over 80% of all deaths globally.Mayor of London Sadiq Khan said, "I'm delighted to be joining mayors from around the world to tackle some of the biggest problems facing our cities.The health of our citizens is a city's greatest asset so I'm taking bold steps to invest in the health of Londoners, such as restricting junk food advertising across the Transport for London network and expanding the ultra low emission zone, which will mean five million more Londoners will be able to breathe cleaner air."These initiatives are not only improving the health of Londoners, but alleviating pressure on our health service and ensuring that future generations can thrive.Improving the health of Londoners will always be at the heart of my vision to build a safer and more prosperous London for everyone.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.355 | 0.116 |
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".