Proceedings of the fifth international ACM conference on Assistive technologies
Bibliographic record
Abstract
ASSETS 2002 is the fifth in ACM's series of conferences sponsored by SIGCAPH. While continuing its traditional focus on assistive technologies, ASSETS 2002 extends the discussions to topics related to Universal Access. Our vision for the conference is to significantly contribute to the scientific knowledge base with an infusion of influential, ground breaking research, design, and evaluation, so that substantial advances can be made by researchers and practitioners who are committed to empowering everyone, universally, with equal access.This proceedings volume is composed of 32 technical papers, contributed by 96 different authors, representing Canada, Chile, England, Greece, Germany, Japan, Scotland, and the USA. The papers are organized into sessions on topics including blindness and vision impairments, hearing and language impairments, motor impairments, cognitive impairments, the elderly, technology access, and speech recognition. The papers were subjected to a competitive peer review process, resulting in an acceptance rate of 36 percent. Thus, the papers that comprise this proceedings volume truly represent the state-of-the-art in this field.As in the past, the conference remains an exceptional forum for researchers, practitioners, educators, and students to present their work as formal papers, as well as engage in interactive dialogue, sharing experiences, accomplishments, and diverse perspectives. In this tradition, Assets 2002 remains a single-track conference, providing meals and social events to encourage informal interactions among participants. Attendees of past ASSETS conferences agree that this format contributed to a very positive, productive conference experience.Another impressive bit of news about ASSETS 2002 - this is the first time that an ASSETS conference has been held in Europe. A quick review of author affiliations makes it clear that this change of venue has attracted many new attendees to the conference. We are confident that by attracting a group of attendees to the conference that are highly representative of this increasingly diverse community, we will realize an even more expedient infusion of new knowledge and ideas into the work that igbeing conducted in this important area.The Conference Organizers, Program Committee and Advisory Panel worked hard to make this conference accessible to all attendees. From the choice of the conference meeting space, to web design, and local arrangements, all efforts have been made to ensure that every attendee will have full access to information and events. If you have feedback about how to improve any aspect of the conference in terms of accessibility, please inform the Conference Chair.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.134 | 0.077 |
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".