Bibliographic record
Abstract
Citation (2015), "List of Contributors", Efficacy of Assistive Technology Interventions (Advances in Special Education Technology, Vol. 1), Emerald Group Publishing Limited, Bingley, p. vii. https://doi.org/10.1108/S2056-769320150000001017 Publisher: Emerald Group Publishing Limited Copyright © 2015 Emerald Group Publishing Limited Melinda Jones Ault University of Kentucky, Lexington, KY, USA Margaret E. Bausch University of Kentucky, Lexington, KY, USA Martin E. Blair University of Montana, Missoula, MT, USA Elizabeth M. Dalton TechACCESS of Rhode Island, Hope Valley, RI, USA Frances Mary D’Andrea Educational Consultant in Visual Impairments, Pittsburgh, PA, USA Carl J. Dunst Orelena Hawks Puckett Institute, Morganton, NC, USA Dave L. Edyburn University of Wisconsin – Milwaukee, Milwaukee, WI, USA Denise J. Frankoff Medstar National Rehabilitation Hospital, Washington, DC, USA Deborah W. Hamby Orelena Hawks Puckett Institute, Morganton, NC, USA Ted S. Hasselbring Vanderbilt University, Nashville, TN, USA Kathy L. Look Howery University of Alberta, Edmonton, Canada Cindy L. Ollis The University of Hawaii at Hilo, Hilo, HI, USA Valerie M. Penton Memorial University, St John’s, Canada Yue-Ting Siu University of California, Berkeley, Berkeley, CA, USA Brian W. Wojcik University of Nebraska at Kearney, Kearney, NE, USA Book Chapters Efficacy of Assistive Technology Interventions Advances in Special Education Technology Efficacy of Assistive Technology Interventions Copyright Page List of Contributors Expanding the Use of Assistive Technology While Mindful of the Need to Understand Efficacy Assistive Technology in Schools: Lessons Learned from the National Assistive Technology Research Institute Research Synthesis of Studies for Promoting Parent and Practitioner Use of Assistive Technology and Adaptations with Young Children with Disabilities Speech-Generating Devices in the Lives of Young People with Severe Speech Impairment: What Does the Non-Speaking Child Say? Students with Visual Impairments: Considerations and Effective Practices for Technology Use Assistive Technology Provision for People with Disabilities in Newfoundland and Labrador, Canada Assistive Technology Standards and Evidence-Based Practice: Early Practice and Current Needs Learning from Experience: Understanding Assistive Technology Knowledge and Skills through an Online Community of Practice Experiences of Families Seeking Funding for Assistive Technologies for Children with Disabilities: Awareness of Legal Mandates Case Study of a State Assistive Technology Fund About the Authors
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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 | 0.004 | 0.038 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.734 | 0.714 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".