Bibliographic record
Abstract
A picture may be worth a thousand words but what might those words be? How do we go about finding those words? Images are often used to convey information, supplement textual content, and/or add visual appeal to documents. Unless the user can see the image and properly interpret it, the user may not receive the same information. While containers exist for providing text alternatives in various types of electronic documents (including Web pages), they are rarely used. When they are used, the text alternatives are not informative. While guidance currently exists regarding which containers to use in order to provide text alternatives, there is little guidance available regarding what information to include in these containers and how to compose text alternatives. The purpose of this work is to establish a procedure for identifying the information being communicated within an image and provide guidance on how to produce informative text alternatives. Based on related information in the areas of Web accessibility, library cataloguing, captioning and audio description, image retrieval and indexing, art description, and tactile representation, important information communicated by an image were identified and a procedure for producing informative text alternatives using that information was developed. Studies were conducted to determine the effectiveness of the procedure to identify important information about an image. Study 1 determined the information identified about an image when the procedure was not available. It also suggested reasons why people would opt to not provide a text alternative for an image. Study 2 determined the information that people would identify when they were given the procedure and a set of questions to help identify information about an image. Study 3 determined the information people identified when they were required to consider all of the different types of information that may be important in an image. The results from these three studies were compared to determine the effectiveness of the procedure to identify important information about the image. Study 4 presented the information identified in the previous three studies to sighted and visually impaired users to evaluate the importance of such information. This study determined the quality of the information identified in the first three studies and the ability of the procedure to identify important information for a wide set of images. The results of these studies showed that the procedure was effective in identifying a greater amount of important information than without the procedure. Additional guidance was also identified to further help people create informative and useful text alternatives. The studies also showed that the procedure could be applied by different user groups to a wide range of images. The procedure was submitted to the International Standards Organization to become a technical specification, which will be available to people around the world.
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 | 0.004 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.025 | 0.007 |
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".