Bridging knowledge, policies and practices across the ageing and disability fields: a protocol for a scoping review to inform the development of a taxonomy
Bibliographic record
Abstract
INTRODUCTION: Bridging is a term used to describe activities, or tasks, used to promote collaboration and knowledge exchange across fields. This paper reports the protocol for a scoping review which aims to identify and characterise peer reviewed evidence describing bridging activities, between the ageing and disability fields. The purpose is to clarify the concepts underpinning bridging to inform the development of a taxonomy, and identify research strengths and gaps. METHODS: A scoping review will be conducted. We will search Medline, Cumulative Index to Nursing and Allied Health Literature, Embase, PsycInfo, Sociological Abstracts and the Cochrane Library, to identify peer reviewed publications (reviews, experimental, observational, qualitative designs and expert commentaries) describing bridging activities. Grey literature, and articles not published in English will be excluded. Two investigators will independently complete article selection and data abstraction to minimise bias. A data extraction form will be iteratively developed and information from each publication will be extracted: (1) bibliographic, (2) methodological, (3) demographic, and (4) bridging information. Qualitative content analysis will be used to describe key concepts related to bridging. CONCLUSIONS: To our knowledge, this will be the first scoping review to describe bridging of ageing and disability knowledge, services and policies. The findings will inform the development of a taxonomy to define models of bridging that can be implemented and further evaluated to enable integrated care and improve systems and services for those ageing with disability. ETHICS AND DISSEMINATION: Ethics is not required because this is a scoping review of published literature. Findings will be disseminated through stakeholder meetings, conference presentations and peer reviewed publication.
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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 | 0.293 | 0.252 |
| Meta-epidemiology (narrow) | 0.006 | 0.007 |
| Meta-epidemiology (broad) | 0.011 | 0.014 |
| Bibliometrics | 0.026 | 0.024 |
| Science and technology studies | 0.009 | 0.011 |
| Scholarly communication | 0.012 | 0.019 |
| Open science | 0.009 | 0.015 |
| Research integrity | 0.019 | 0.014 |
| Insufficient payload (model declined to judge) | 0.054 | 0.023 |
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".