The development of the International Classification of Functioning, Disability and Health Core Sets for deafblindness: A study protocol
Bibliographic record
Abstract
BACKGROUND: Individuals with deafblindness experience a combination of hearing and vision impairments. The World Health Organization has developed a global framework referred to as the International Classification of Functioning, Disability and Health (ICF) to describe health and functioning. From the full ICF classification, a selection of categories, referred to as ICF Core Sets, provide users with a tool to describe functioning and disability in specific health conditions. There has been no ICF Core Set created for deafblindness. Given that core sets are instrumental in improving clinical practice, research, and service delivery, the aim of this study is to develop an ICF Core Set for deafblindness. METHODS: As part of the preparatory phase in the ICF Core Set development, there are four studies that will be conducted. This includes the [1] systematic literature review that examines the researcher's perspective, [2] qualitative study focusing on the individuals with deafblindness experience, [3] experts survey that looks at health professional's perspective, and [4] empirical study that examines the clinical perspective. The studies will be conducted using the principles outlined by the ICF Research Branch for the development of ICF Core Sets. The systematic literature review protocol was submitted for registration on PROSPERO CRD42021247952. DISCUSSION: An ICF Core Set created for deafblindness will benefit individuals living with deafblindness who are often excluded from social participation, policies, and services. An ICF Core Set for deafblindness will have a significant impact on healthcare professionals, policymakers, researchers, service providers and individuals with deafblindness by facilitating communication among all stakeholder to support the functioning of those with deafblindness.
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 | 0.147 | 0.107 |
| Meta-epidemiology (narrow) | 0.003 | 0.005 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.055 | 0.014 |
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".