How to decipher the MS?

[magnesium]

Here are some necessary, but certainly insufficient, steps involved in solving the MS.

1) Be aware of all assumptions you are making, also any unconsicious ones. The last part is, by its very nature, not easy. 
Example: if you assume it is a cipher, you must be aware that you probably won't find the solution if it is not not a cipher. If you assume there is a plaintext in Latin, you may not find the solution if there is an Arabic plain text.
It is not forbidden to make any assumptions at all. One just has to be aware what are the consequences of them.

2) Be aware of the various statistical analyses that have been made in the past, and what they already tell us. 

3) Make sure you have another hobby that brings occasional moments of achievement. ;-)

That's really it. The advice from my web site, that was quoted in the opening post, does not lead to any specific steps to be taken, but always keep it in mind when working on it.

There's a lot of wisdom in René's advice. 

My general perspective here is that it would be more probable for us to see the one and only VMS with the statistical properties it has if the underlying text generation method often and reliably created VMS-like text. So as I see it, the question is, which specific kinds of text generation methods have high probabilities of generating text with VMS-like properties? Exploring these parameter spaces will yield reference models for how the text could have been generated. None will be perfect—but a model doesn't have to be perfect to be analytically useful. What are a good model's specific modes of failure when it comes to replicating the VMS, and what does that failure tell us? What are the general predictions that a good model makes regarding the nature of the VMS, and what happens when those predictions are tested?

Some non-exhaustive ideas:

1. Gibberish hypothesis

Timm and Schinner (2020)'s self-citation algorithm elegantly shows that the iterative generation of meaningless text can go a long way toward replicating the VMS's statistical properties, but it would be interesting to test the four corners of what this kind of algorithm can do. For instance, I'd love to see someone systematically sweep through different combinations of threshold parameters and initializing lines to study the broad behavior of this class of algorithm. Under what specific conditions does this general kind of algorithm deliver especially VMS-like text? 

2. Ciphertext hypothesis

The Naibbe cipher has the structure it has specifically because I was looking for probabilistically favorable ways to structure a homophonic substitution cipher that could generate VMS-like text when encrypting a European language. I came away from that process—especially my work with my random cipher-generation tool Voynichesque—convinced that the VMS's observed word grammar, character entropy, conditional character entropy, token length distribution, and word type length distribution jointly place major constraints on plausible cipher structures. For one, a substitution cipher must be verbose to have a prayer of exhibiting VMS-like behavior while encrypting most any European language.

But are there other kinds of historically plausible ciphers that can evade these constraints? For example, in 2009 Nick Pelling suggested that a clever multi-step transposition cipher could explain some features of the VMS: You are not allowed to view links. Register or Login to view. One could imagine screening many randomly generated variations of Pelling's proposed cipher for VMS-like properties as they all encrypt a conserved plaintext. Under what specific conditions does a Pelling-style ciphertext do a better or worse job of mimicking the VMS?

Similarly, Matlach, Janečková, and Dostál (2022) proposes a steganographic cipher, in which one plaintext letter is mapped to a sequence of 3 numbers (111, 123, 221, etc.), several Voynichese glyphs each stand for 1 number, and some apparent glyphs are really ligatures that stand for sequences of 2-3 numbers. When screening across a wide range of plaintext languages, what are the number sequence assignments, glyph assignments, and plaintext languages that combine to most reliably yield VMS-like text? What are the other properties of those ciphertexts, and to what extent are they consistent with the VMS?

3. Chinese language hypothesis

Jorge Stolfi and others have proposed that the unusual properties of Voynichese stem from a one-off attempt to develop a phonetic writing system for an East Asian language. Can we define a representative list of possible phoneticization schemes and then randomly iterate phoneme-glyph mappings for a variety of East Asian languages, to see under what conditions we get more VMS-like text?

The point here is, we need to treat the VMS's statistical properties as constraints and then figure out which kinds of text generation methods often evade those constraints.