BUILDING INTERDISCIPLINARY RESEARCH CAPACITY: LESSONS FROM THE INTERNATIONAL SUMMER SCHOOLS ON AGING
Bibliographic record
Abstract
The objective of this symposium is to consider the rationale, delivery and outcomes of an International Summer School on Ageing (ISSA) for doctoral students and post-doctoral fellows, held in 2012 (Italy), 2014 (Sweden) and 2016 (Canada). The creation of the ISSA is a direct response to the “Road Map for European Ageing Research” (Walker et al., 2011), produced by the European Commission’s FuturAGE project. ISSA is unique in its interdisciplinary approach, international audience (of both participants and mentors), and focus on ageing-related contents as well as methodological and research development issues. We analyse the outcomes of three ISSA. Data are based on participants’ assessments at the end of each and then six months post-ISSA (six data-sets totally). The perspectives of several ISSA alumni (among its 60 graduates) reflect different national and disciplinary (including clinical) contexts in appraising ISSA’s short- and longer-term impacts. Findings underscore the value of role-modelling through interaction with established researchers and the development of international research networks, leading to active interdisciplinary collaborations. This symposium also contextualizes approaches to the future of interdisciplinary education on ageing, comparing ISSA with other national and international initiatives. The training of early career researchers remains often largely mono-disciplinary, thus challenging researchers’ professional capacities to understand the holistic nature of the ageing process. ISSA underscores instead the value of additional interdisciplinary training within an international framework. The FuturAGE project leader, Alan Walker (UK), is discussant, and will highlight how initiatives like ISSA can play a strategic role in capacity building in ageing research.
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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 | 0.102 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.023 | 0.025 |
| Scholarly communication | 0.020 | 0.026 |
| Open science | 0.005 | 0.048 |
| Research integrity | 0.006 | 0.014 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".