Bibliographic record
Abstract
“People cannot achieve their fullest health potential unless they are able to take control of those things which determine their health” declares the Ottawa Charter, the founding statement on the promotion of health from the World Health Organization (1986).1 Yet to “take control” of the determinants of health—such as the obesogenic risks in the environment—can be hard for any person, but perhaps especially hard for younger people, who may have neither the resources nor the political influence to challenge the status quo. The first step is to recognize the value of youth involvement in the process of designing and implementing policies concerning obesity. Young people from across the globe truly have bright and innovative ideas that, of course, may sometimes differ from those of adults, but are by no means less valuable due to the fact that youngsters have their own unique perspective on the matters that the older generations are currently dealing with. Furthermore, young people such as myself will live with the results of those policies in the upcoming decades and therefore, it is crucial for us to get a chance to have an impact on our future. When it comes to health-related policies, young people are particularly interested because more and more teenagers suffer from, for instance, obesity or diabetes. Additionally, a common interest in these topics may be observed these days because youngsters—in general—have acquired a clear understanding of the importance of leading a healthy lifestyle. To give an example, I myself am a type 1 diabetic and that is why I have been familiarizing myself with the disease, healthy nutrition/lifestyle, and the general situation of people coping with diabetes or any complications of it in my country for the past 6 years. Indirectly, this is also the main reason why I decided to join the CO-CREATE Youth Declaration Task Force (see www.co-create.eu) when the opportunity of applying for a place in the program arose—I wanted to share the knowledge that I had previously gained. Even though the declaration may and should be further improved, we strongly believe that these four statements—if implemented by policymakers and other stakeholders—would drive change in the field. However, we cannot make these changes alone. We are not able to act without any help from the authorities and that is exactly why we want to be heard, carefully listened to, and included in the process of bringing the demands into effect. Then, together, we can truly “take control” and influence not only the present, but also the future.
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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.009 | 0.009 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.026 | 0.008 |
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".