Editorial: Development, Wellbeing, and Lifelong Learning in Individuals With a Dual Sensory Loss
Bibliographic record
Abstract
Although "dual sensory loss" is recognized as a unique disability (European Parliament, 2004), meaning that everyone with deafblindness has the right to specifically tailored education and rehabilitation, policies and practices are nevertheless fragmented.Research on deafblindness is still lacking.This Research Topic, with a collection of the latest original research findings, will serve to bridge the gap between theory and practice thereby strengthening professionals' knowledge, institutions, and systems in their mission to support wellbeing, development, and lifelong learning of people with dual sensory loss.The current fragmentation of policies and practices is the result of several reasons.Significantly, dual sensory deprived individuals can be divided into three subgroups with their own focus areas.Classification is mainly attributable to the onset of the dual sensory loss: (a) Congenital deafblindness: from birth; (b) Acquired deafblindness: after language acquisition (during infancy, puberty or young adolescence); and (c) Age-related deafblindness: affecting individuals over 50, due to aging (Jaiswal et al., 2018); or as a result of a syndrome.Many syndromes can lead to deafblindness, CHARGE syndrome being the most common for congenital deafblindness, and different types of USHER syndrome for acquired deafblindness (Regenbogen and Coscas, 1985).The goal of this Research Topic was to contribute to the "cutting edge nature" of research on dual sensory loss and reunite the three fields within deafblind education and rehabilitation.Each of the 20 papers that are included have contributed toward meeting this goal, covering themes which can be divided in four main clusters, namely (1) wellbeing and health;(2) communication, learning, and access to information; (3) importance of assistive technology; and (4) research, professionalization and support.In addition to papers reporting original research, this Research Topic also includes several review and theory articles, giving us new empirical evidence and innovative ideas for practical approaches.
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 | 0.007 | 0.029 |
| Meta-epidemiology (narrow) | 0.005 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.021 | 0.020 |
| Insufficient payload (model declined to judge) | 0.013 | 0.009 |
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".