Bibliographic record
Abstract
Health promotion is very relevant today. There is a global acceptance that health and social wellbeing are determined by many factors outside the health system which include socioeconomic conditions, patterns of consumption associated with food and communication, demographic patterns, learning environments, family patterns, the cultural and social fabric of societies; sociopolitical and economic changes, including commercialization and trade and global environmental change. In such a situation, health issues can be effectively addressed by adopting a holistic approach by empowering individuals and communities to take action for their health, fostering leadership for public health, promoting intersectoral action to build healthy public policies in all sectors and creating sustainable health systems. Although, not a new concept, health promotion received an impetus following Alma Ata declaration. Recently it has evolved through a series of international conferences, with the first conference in Canada producing the famous Ottawa charter. Efforts at promoting health encompassing actions at individual and community levels, health system strengthening and multi sectoral partnership can be directed at specific health conditions. It should also include settings-based approach to promote health in specific settings such as schools, hospitals, workplaces, residential areas etc. Health promotion needs to be built into all the policies and if utilized efficiently will lead to positive health outcomes.
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 | 0.015 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.009 | 0.010 |
| Insufficient payload (model declined to judge) | 0.023 | 0.009 |
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".