The digital development within society that persons of 75 years and older in European countries have been part of: A scoping review protocol
Bibliographic record
Abstract
Over the past decades countries of the world have experienced increase in the share of older people in demographics and the number is expected to rise even more. People are becoming more than ever dependent on digital technologies. The aim of this study is to map the body of literature concerning historical digital development over the last 20 years that people of 75 years and older in European countries have been part of. Moreover the goal is to identify research gaps in the existing literature in order to inform future research. The five-staged Arksey and O’Malley methodology framework is used to guide the scoping review process. Research strategy and eligibility criteria are defined. The study selection is made based on the eligibility criteria. A framework developed for the scoping review informs the charting of data from the included studies. Results will be summarized with criteria relevant for policy-makers, healthcare providers and the public.
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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 | 0.115 | 0.081 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.007 | 0.009 |
| Bibliometrics | 0.016 | 0.012 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.039 | 0.012 |
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".