Therapeutic Issues and Adolescent Cochlear Implant Recipients
Bibliographic record
Abstract
No AccessPerspectives on Hearing and Hearing Disorders in ChildhoodArticle1 Oct 2004Therapeutic Issues and Adolescent Cochlear Implant Recipients Patricia M. Chute and Helen C. Buhler Patricia M. Chute Mercy CollegeDobbs Ferry, NY Google Scholar More articles by this author and Helen C. Buhler Mercy CollegeDobbs Ferry, NY Google Scholar More articles by this author https://doi.org/10.1044/hhdc14.2.16 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationTrack Citations ShareFacebookTwitterLinked In References Learning about adolescent students (2001). Manitoba Education and Youth. Retrieved May 21, 2004, f r o m http://spectrum.troyst.edu/~mjparker/adolescent.htm Google Scholar Ling, D. (1989). Foundations of spoken language for hearing-impaired children.Washington, DC: Alexander Graham Bell Association for the Deaf. Google Scholar Perusse, M.,Bernstein, A., & Philips, A. L. (1992). Incorporating speech development into an educational program.Volta Review,, 94, 79–94. Google Scholar Stout, G. G., & Windle, J. V. (1992). The developmental approach to successful listening II.Houston, TX: Houston School for the Deaf. Google Scholar Wiig, E. (1989). Steps in language competenc.Developing metalinguistic strategies. San. Antonio, TX: The Psychological Corporation. Google Scholar Blood, G. W.,Blood, M., & Danhauer, J. L. (1977). The hearing aid “effect.”.Hearing Instruments, 20, 12. Google Scholar Brown, A., & Campione, J. (1990). Communities of learning and thinking, or a context by any other name.In D. Kuhn (Ed.), Developmental perspectives on teaching and learning thinking skills (pp. 108– 126). New York: Karger. Google Scholar A. K. Cheng & J. K. Niparko (2000). Analyzing the effects of early implantation and results with different causes of deafness: Meta analysis of pediatric cochlear implant literature. In J. Niparko (Ed.).Cochlear implants: Principles and practice (pp. 259–265). Philadelphia: Lippincott Williams and Wilkins. Google Scholar Crais, E. (1990). Word knowledge to word knowledge..Topics in Language Disorders, 10 (3), 45–62. Google Scholar Gray, C.(1995b). The original social storybook.Arlington, TX: Future Horizons. Google Scholar K. I. Kirk (2000). Challenges in the clinical investigation of cochlear implant outcomes. In J. Niparko (Ed.).Cochlear implants: Principles and practice (pp. 225–259). Philadelphia: Lippincott Williams and Wilkins. Google Scholar Larsen, V. L. & McKinley, N. L., & Boley, D. (1993). Service delivery models for adolescents with language disorders. Language, Speech, and Hearing Services in the Schools,, 24, 36–42. Google Scholar Larson, V. L., &McKinley, N. (1995). Language disorders in older students.Preadolescents and adolescents. Eau Claire, WI: Thinking Publications. Google Scholar Larson, V. L., &McKinley, N. L. (2003). Communication solutions for older students.Assessment and intervention strategies. Eau Claire, WI: Thinking Publications. Google Scholar Nevins, M. E., & Chute, P. M. (1996). Children with cochlear implants in educational settings.San Diego: Singular. Google Scholar Nippold, M. (2000). Language development during the adolescent years:Aspects of pragmatics, syntax, and semantics.Topics in Language Disorders, 20 (2), 15–28. Google Scholar Nippold, M. (1993). Developmental markers in adolescent language: Syntax, semantics, and pragmatics..Language, Speech, and Hearing Services in the Schools, 24 (1), 21–28. AbstractGoogle Scholar R. Paul (2001). Language disorders from infancy to adolescence.2nd ed.). Philadelphia: Mosby. Google Scholar Rose, D.,Vernon, M., & Pool, A. (1996). Cochlear implants in prelingually deaf children.American Annals of Deaf, 141, 258–262. Google Scholar Silliman, E., & Wilkinson, L. (1991). Communication for learning: Classroom observation and collaboration.Gaithersberg, MD: Aspen. Google Scholar Whitmore, K. (2000). Adolescence as a developmental phase: A tutorial.Topics in Language Disorders, ( 20 (2), 1–14. Google Scholar Additional Resources FiguresReferencesRelatedDetails Volume 14Issue 2October 2004Pages: 16-20 Get Permissions Add to your Mendeley library History Published in issue: Oct 1, 2004 Metrics Topicsasha-topicsasha-article-typesasha-sigsCopyright & Permissions© 2004 American Speech-Language-Hearing AssociationPDF DownloadLoading ...
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 | 0.001 | 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 | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 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".