Constructions of ‘sound’ in scientific discourses about cochlear implants
Bibliographic record
Abstract
The linguistic resources employed to discuss sensory experiences and phenomena can vary considerably between different cultural, disciplinary and socio-political contexts. Whilst questions about the discourses of sound have long been explored in some fields, within the field of cochlear implant research, such questions have received limited attention. This article draws together literature from diverse fields, highlighting the various complexities inherent in talking about “sound” in different contexts. The results of a collocation analysis of “sound” within the CIRCorpus - (a purpose-built 3-million-word corpus comprised of scientific research articles about cochlear implants published between 1960 and 2024) are then reported. The collocation analysis highlights a discursive environment in which sound is predominantly framed within a language of testing and abilit y, suggesting that discussions of sound within CI research have become distinctly psychologized and increasingly technicalized and homogenized over time. The implications of these patterns for informing future CI research agendas are discussed.
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 | 0.030 | 0.072 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.010 | 0.007 |
| Science and technology studies | 0.013 | 0.040 |
| Scholarly communication | 0.013 | 0.015 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".