Zwischen politischen Zielen und niedrigschwelliger Umsetzung: Chancen und Herausforderungen der Digitalisierung in der settingbezogenen Gesundheitsförderung – Ein Erfahrungsbericht der Landesvereinigu...
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
During the digital transformation, settings are changing deeply in their processes, structures and culture, and new opportunities and challenges are emerging for setting-based health promotion and prevention.This requires a new conceptual understanding of digitalized settings that can address these changes.Based on the setting approach of the World Health Organi zation and the underlying understanding of settings as organizations with formal structures, a critical analysis and definition of terms is provided.Subsequently, intervention logics according to the setting approach in digi talized settings are presented. EinleitungMit der digitalen Transformation gehen Vernderungen in allen Gesell schafts-und Lebensbereichen einher. 1 Es kommt zu Vernderungen von Arbeitsprozessen oder Organisationsstrukturen und der Alltag in Settings wird geprgt.Durch digitale Mglichkeiten der Vernetzung und Kommu nikation zwischen Settingmitgliedern sind ebenso die Gesundheitsversor gung sowie die Gestaltung von Angeboten der Gesundheitsfrderung und Prvention von tiefgreifenden Vernderungen betroffen. 2or diesem Hintergrund stellt sich zum einen die Frage, wie Struktu ren von bestehenden Settings, im Sinne der Definition der World Health Organization (WHO), im Zuge der digitalen Transformation gesundheits frderlich gestaltet werden knnen.Zum anderen stellt sich die Frage, ob sich durch die Vernderungen der digitalen Transformation neue Settings herausbilden, die im Sinne des Settingansatzes der WHO als Settings de finiert werden knnen und als praktische Konsequenz in den Leitfaden
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.
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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 0.022 |
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 it