Driving the life course approach to vaccination through the lens of key global agendas
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
Globally, our population is ageing at an unprecedented rate and by 2030, which marks the end of the United Nations (UN) Decade of Healthy Ageing, the number of people aged 60 years and older will be 34% higher than today, reaching 1.4 billion. Vaccination is one of the most effective public health interventions of modern times and a key action in fostering healthy ageing throughout the life-course. To promote wellbeing at all ages, global agendas including the WHO Immunization Agenda 2030, the UN Decade of Healthy Ageing and the World Health Organization (WHO) Global Report on Ageism outline strategic actions and guidance to help implement policies and programs. Yet, the linkages between healthy ageing, functional ability and adult vaccination are not substantively recognized or integrated as cross-cutting themes, which impacts operationalization into national immunization plans. When aligned and connected strategically, these agendas have potential to substantially contribute to policy change to prioritize life-course immunization and support the preservation of function at all stages of life. This article describes the intersecting goals and visions of these strategic agendas and identifies specific elements of overlap, which when connected, could strengthen the development of comprehensive and effective national immunization policies.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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