-
Notifications
You must be signed in to change notification settings - Fork 1
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Errata #2
Comments
Thanks for the comments! I think it is valuable to get your position on these claims.
Yes, this was misleading. I was using
The numbers were from an older version of the coverage script. I aligned them with the current script in b39fb7a. So now they also match the numbers from analysis.md.
Thanks for the feedback! I will have to look into that. I opened the separate issue w3c/wcag#5 for more focus.
The images you posted are far from obvious evidence, at least for me. I am not sure why you treat them as such.
As others have already said, none of that qualifies as scientific evaluation or peer review. So I will stand by that sentence. Thanks again for your comments and also for the work on APCA. I learned a lot from it already and hope my contributions are helpful. |
The "others" don't understand terms such as "efficacy" and "peer review" and are applying the narrow FDA meaning which is notwithstanding, not the general scientific meaning. From what I gather, they are parroting terms they heard on the news during the early days of COVID. APCA is a practical application of peer reviewed, scientific consensus CAM models and readability research, as detailed in the bibliography. Claims otherwise are nothing more than trolling. |
I am quoting the "Missing Introduction" below, indicating misunderstandings and errors:
As well as for use in other standards and contexts.
Your demo as linked here is not fully compliant with APCA. Please see: https://git.apcacontrast.com/documentation/minimum_compliance
More correct: APCA produces a value of 0 to 106 for dark text on a lighter background, and 0 to -108 for light text on a darker background.
Developers have the option of returning a signed value to indicate polarity, OR returning a value with a string identifying the polarity. I.e.:
Signed value: 75 or -75
Text Ident: 75 BoW or 75 WoB
Text Ident: 75 LM or 75 DM
etc.
There is no contrast requirement for level A, so I'm not sure what you are referring to. Also, how did you derive these numbers? They don't seem correct?
Your examples as chosen are all fairly high contrast using a bold font. This does NOTHING to demonstrate the differences. Your examples are mostly in the realm of "contrast constancy", and not near the edge.
No not really, though there are contrast sensitivity impairments that do have an effect.
Ambient lighting affects contrast perception in that ambient is part of the driver of light adaptation, and the adapted level affects contrast perception, as does context. All of these issues though are part of the contrast matching experiments that instructed the curve shaping that was done in developing APCA, and are set to the "lowest common worst case".
Actually, it is prima facie evidence, and trivial to demonstrate. Here's an example:
And here is a comparison for dark mode:
Your examples are poor, using a bold font, and using high contrast, the result is that your examples are above contrast constancy, and therefore do not demonstrate the important differences.
??? There has been ample third party and peer review. Here are just a couple
It is true there are uninformed claiming otherwise, and they fully ignore the reviews that have been completed. Also, ACPA is the result of three years of development in the Visual Contrast subgroup of Silver, and under the oversight of the AGWG.
LOL. You never bothered to look in the folder labeled "documentation", the first file in the list is the algorithm. Not to mention that the JS file shows the algorithm plain as day, along with ample comments.
You are by your own admission not a vision scientist. "Perceptually uniform" has a specific meaning in the context of the field, namely that that the delta value matches the perceived delta.
WCAG 2 contrast math is nowhere close to perceptual uniformity, as is plain to see in the above examples.
Perceptual uniformity means, in this context, that a lightest pair of colors at Lc 45 is just as readable as a darkest pair of colors also at the wsame Lc 45.
Thread 695 is over three years old, and is not a good place to start. The documentation readme you linked to is fine, but the catalog of resources is https://git.myndex.com
Thank you for reading.
The text was updated successfully, but these errors were encountered: