[Blog Post] Was the Voynich text generated by using the self-citation-method?

[RenegadeHealer]

The problem with an explanation which relies on the scribe being "aesthetically motivated" is that it effectively puts the process in a closed box we can't open. We can't judge aesthetics objectively, so will never know why [lk] is so much more pleasing than [lt], or just what bothered the scribe about [pe] and [fe], or why [ych] is pretty at the start of a line but ugly elsewhere...

Emma, I hear you making two distinct points:

1. Torsten’s autocopy self-citation algorithm is logically circular. A just-so story. It invites special pleading along the lines of “That’s just what the guy felt like doing”.
   
2. The odds of a scribe or small team of scribes in the early 1400s writing >200 pages of asemic writing with all the statistical properties of the VMs text, is so vanishingly small as to be justifiably ruled out.
   

I’m with you on point number 1. I agree with Timm and Schinner that a stochastic process generating asemic writing could account for the VMs text. They’ve led me to the opinion that a VMs text without meaning is the proper null hypothesis for all attempts to find meaningful information in it. It’s another thing entirely, though, to claim that their algorithm was that which generated the VMs. That’s an easy claim to defend, when the steps to the algorithm are vaguely described and stretchy enough to fit any composition of a large amount of uniform and convincing asemic writing, and when the burden of proof isn’t even on you to begin with.

I disagree with point number 2. As Marco’s post alludes to, the idea that the output of the task of producing long-form random gibberish one line at a time will show statistically significant trends across human populations — which are complex, consistent, and anything but random — is not at all far-fetched to me. It’s likely that some or all of these hypothetical statistical metrics also correlate with certain types of meaningful information strings. But I could see long-form deliberate pseudo-language having a few distinct profiles of statistical metrics, with very good positive and negative predictive value for it.

A problem here is priming. As of now, too little is known about what environmental factors have large effects on any given person’s attempts and long form asemic writing, let alone speculate on which if any of these constraints the VMs text’s composer(s) worked under.