Bibliographic record
Abstract
Here we report on the EU FP7 Coordinating Action entitled BRAID or Bridging Research in Ageing and ICT Development which aims to develop a comprehensive research and technological development roadmap for active ageing by consolidating existing roadmaps and by describing and launching a stakeholder co-ordination and consultation mechanism. A roadmap describes a program for future research and development indicating research gaps and what might be developed and when. This roadmap characterises key research challenges and produces a vision for a comprehensive approach in supporting the well-being and socio-economic integration of increasing numbers of senior citizens in Europe.BRAID responds to the clear need to consolidate the various existing perspectives, plans, roadmaps and research and to coordinate effectively the stakeholders in ICT and Ageing. It will utilise knowledge repositories and stakeholder networks to create a self-sustaining, dynamic strategic mechanism for overcoming the fragmentation that has plagued e-inclusion and for improving co-ordination and collaboration among stakeholders. This project aims to create a dynamic ICT and Ageing roadmap that addresses older people's needs not otherwise well met, that identifies and benefits from best practices in the EU and elsewhere and that analyses current and potential gaps in knowledge and execution. It further aims to instantiate a strategic research agenda that tracks and builds upon existing, emerging and disruptive technologies and that responds to the changing socio-economic conditions of stakeholders. Finally, we aim to expand the BRAID networks of contacts to build a self-sustaining co-ordination mechanism, which is viral and ubiquitous and reaches out across the heterogeneity of stakeholders.BRAID builds upon the experience and knowledge developed in previous projects while taking account of e-inclusion efforts in the EU27 as well as Australia, Canada, Japan and the US. We will further describe our first steps in the development of our BRAID community portal based on BRAIDbook our enhanced social networking community tools for knowledge dissemination.
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 | 0.044 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.006 | 0.018 |
| Scholarly communication | 0.021 | 0.027 |
| Open science | 0.002 | 0.031 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".