Deaf Cultural Identification, Cochlear Implants, and Life Satisfaction
Bibliographic record
Abstract
Cultural identification within the Deaf community is a new field of research that looks at the differences in acculturation between deaf individuals. Glickman (1993) created a Deaf Identity Development Theory, which outlines that deaf individuals either identify with the hearing community, the deaf community (immersion), both communities (bicultural), or do not necessarily identify with either (marginal). Research has not looked directly at the effects cochlear implants (CI’s) have on the overall life satisfaction and well-being of these individuals and how the implants may create changes to their cultural identification. This study examined the link between cochlear implants, Deaf cultural identification and overall life satisfaction within the Deaf community and hypothesises that individuals with cochlear implants and strong culture identification will show significantly higher levels of overall life satisfaction than those who do not. A sample of deaf individuals ages 18 and older were given three measures: the Deaf Identity Development Scale (DIDS), the Deaf Acculturation Scale (DAS) and the Satisfaction with Life Scale (SWLS). The results found a significant correlation between life satisfaction and cultural identification, but no significant correlation between CI’s and life satisfaction or cultural identification.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".