The EU project VAXaction: tacking effectively vaccine hesitancy in Europe
Bibliographic record
Abstract
Abstract The main objective of VAX-ACTION is to support EU Member States and relevant stakeholders to implement the results of tailored, evidence-based interventions aimed to reduce vaccine hesitancy. Based on the evaluation of effectiveness of these interventions, which will be conducted in selected target regions in EU member states, recommendations will be drawn through diverse dissemination strategies to allow scaling up good practices to other member States, but also to the USA and Canada, where gaps in implementation strategies also have prevented effective, evidence-based interventions aimed to better deal with vaccine hesitancy. The first phase of the research involved some relevant systematic reviews with the aim of: 1. to map public health evidence and research results on large-scale vaccination programs in Europe and north America; 2. to map interventions aimed to address vaccine hesitancy regarding new and well-stablished vaccines and vaccination programs (Covid-19, mpox, national immunizations programs for children) in Europe and north America; 3. to identify successful and unsuccessful interventions designs aimed to address vaccine hesitancy, including challenges in the implementation, evaluation designs, and the feasibility of scaling-up solutions that are context-sensitive; 4. to identify significant similarities or dissimilarities in the designs and outcomes of interventions aimed to address vaccine hesitancy in northern countries where political and academic concern towards this phenomenon is growing; 5. to identify the extent to which ‘grounding’ (bottom-up) experiences aimed to address vaccine hesitancy are evidence-based, build on current international knowledge and guidelines, and whether they are internationally reported; 6. to systematize the mapping of interventions aimed to address vaccine hesitancy in the northern hemisphere in a way that can be shared and used by third parties. This contribution will illustrate the results of the first phase of the project.
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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 | 0.051 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".