ARIA Channels: ReefChat and Fire Vox as a Case Example
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Web 2.0 enabled by the Ajax architecture has given rise to a new level of user interactivity through Web browsers. Many new and extremely popular Web applications have therefore arisen, some examples being Google Maps, Google Docs, Flickr, and so on. Unfortunately, the accessibility support in most Ajax applications overall is lacking. WAI-ARIA markup for live regions and channels presents a solution whereby these applications can be made accessible. To address this problem, our team developed an accessible Ajax chat application called ReefChat and added support for ARIA live regions to Fire Vox, a talking browser extension for Firefox. Highlighted features include: (a) chat message notification through live regions to notify the AT, (b) enabling keyboard access for moving to the next and previous messages in the chat transcript area, and (c) enabling keyboard access to jump to the next and previous messages from specific users. In this article, we will open with a brief discussion of the challenges of making Web 2.0 applications accessible to visually impaired users and will then describe ReefChat and Fire Vox. KEYWORDS: Human factorsdesignaccessibilityWeb 2.0AjaxARIALive RegionsUser Agents ACKNOWLEDGMENTS We thank the Mozilla Foundation for funding our projects and research. We also thank Erin Russell for her helpful comments and suggestions and for proofreading a draft of this article.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it