Croatian toponyms

[FlatAssembler]

I think you are forgetting the question that you asked, which is whether you can get this paper published. The answer, as far as I can see, is "Yes", though I do not know where you could publish it. If you write in English, you would have available a much larger collection of outlets available. Furthermore, remember that "publish" means "make public", and right now you have the ability to publish this article (since you use github, I'm pretty sure you know how). Even if you don't want to self-publish, there are many people who are willing to publish for you for a modest fee.

Perhaps you want to publish for free in a journal with a good reputation. Linguistic Inquiry is an example, but I don't think there is any chance they would publish it even if you submitted an English version – they would reject it on subject-matter grounds. You could submit to other journals (Cognition, The Lancet, JASA, IJAL which would also reject it on subject-matter grounds, not even sending it out for review. You have to first identify some set of plausible venues, and then write appropriately for that journal. This has been my practice for decades – figure out a general topic, figure out who might publish it, then write in a manner appropriate to that journal (there can be only one: but if you are rejected, you pick another, and re-write).

You might publish in a journal like https://www.komunikacijaikultura.org/index.php/kk: there are almost a thousand that you can pick from at https://www.scimagojr.com/journalrank.php?category=1203&year=2018&page=18&total_size=864. This is by no means complete – I know of a number of excellent journals that are not included.

Since you reject traditional academic methodology, you should expect that journals that presuppose that methodology will reject you. So you have to first shop for a journal that does not care whether you have established the truth of your claim relative to competitor accounts, and does not care that you have clearly explained the issue and your solution in a fashion that others can judge the truth of your claims. You need to find a journal where readers are willing to take your claims on faith. Or, one where readers already share your particular beliefs and experiences. I claim that you are wrong about κορακινος meaning goldfish or any other fish or that it comes from Egyptian, so I reject a crucial step in your argument – so just look for a journal with readers who will not nitpick over factual claims.

"Korakinos" did denote some fish living in Nile river, that is, AFAIK, not controversial: https://en.m.wiktionary.org/wiki/coracinus

[FlatAssembler]

Please stop spamming, @waive15! Your links seem to have absolutely nothing to do with the topic!

[Daniel]

(It wasn't spam, but it was also not clearly on topic. Waive15 removed the post on request, which I think makes sense because in this section of the forum the user posting the original thread should be able to generally set the topic of discussion. But I don't think the post was intended to be disruptive. Regardless, you can carry on with the discussion now.)

[FlatAssembler]

I have made a presentation which I will, if everything goes right, present in the castle in Donji Miholjac at the end of April or beginning of May: https://flatassembler.github.io/Karasica.ppt

[FlatAssembler]

What do you think, is it likely that this k-r root meaning "to flow" in the Croatian toponyms is not etymological root, but rather a phonosemantic root? I don't know which claim is more extraordinary. If I claim it is an etymological root, then I am saying the mainstream interpretation of the Croatian toponyms is wildly wrong (which I am not sure is such an extraordinary claim, as the mainstream interpretation of Croatian toponyms seems to be based on groupthink more than evidence). If I claim it is a phonosemantic root, then mainstream etymology of Croatian toponyms can still be correct, but then I am saying some weak form of the phonosemantic hypothesis is correct. As far as I understand, the vast majority of linguists would consider even a weak form of the phonosemantic hypothesis a very extraordinary claim.

[FlatAssembler]

I'm not familiar enough with that approach to comment. This is one of the reasons why I've recommended working in an established, well-known methodology.

I must admit I do not understand what is the point of trying to achieve something using an "established" methodology. The fact is, if some methodology has been tried again and again, every time resulting in a failure, isn't that a sign that you should try something at least slightly different, rather than that you should once again try the same thing and hoping to get a better result?

[Daniel]

It's absolutely crucial for productive research!
1. You can talk to other researchers, and you will understand each other.
2. It makes your work replicable and verifiable.
3. The methods have worked over and over again (unlike what you claimed), so they are a reliable way to consider a new question, new data, etc.
4. New/different isn't necessarily better.
5. Methodological innovations are occurring all the time, but in small steps, not just throwing out established practices because you feel like it. If it works, don't break it. If it doesn't work, adjust a bit until it does.

Ultimately, we circle back to the same original problem: you're trying to find a way to prove your answer correct, rather than conducting an unbiased, principled scientific search for the correct answer. If established methodologies do not get you to the answer your expect, that may be a feature, not a bug: maybe you're expecting the wrong answer.

(I should say, I think say again, that I'm not confident your answer is incorrect. I just don't know that it is correct, or that there is a reliable methodology to support it. You're reaching for something difficult, and it may just be out of reach.)

Good luck with your upcoming conference talk! That's great, and I hope you get useful feedback. The good news is that what we think here doesn't matter much anymore. See how the conference goes. But remember that to communicate with other researchers, you need to speak the same language (by which I mean methodology that is at least comprehensible, and hopefully comparable).

[panini]

I'm not familiar enough with that approach to comment. This is one of the reasons why I've recommended working in an established, well-known methodology.

I must admit I do not understand what is the point of trying to achieve something using an "established" methodology. The fact is, if some methodology has been tried again and again, every time resulting in a failure, isn't that a sign that you should try something at least slightly different, rather than that you should once again try the same thing and hoping to get a better result?

There is an established methodology for determining "how much stuff you have", for example sand, water, meat etc. It is based on a physical theory, involving force, mass, gravity and so on. The reason for using that methodology is that it works. There is an alternative methodology where you use sticks of fixed length and lay the sticks by the stuff (measure the volume), that also works, but it tells you something totally different (volume, not weight). There is a fundamental connection between method and theory.

An "established methodology" should be used until it is proven that an alternative methodology gives better results. That is really the only scientifically legitimate reason for following method A versus B. There is an article of faith in following a methodology based on popularity – you are assuming that other practitioners are not deluding themselves. It is very well established in linguistics that we are capable of large-scale self-delusion. Therefore, you have to decide whether your alternative methodology is actually superior to the standard method. You have to be willing to accept being ignored if you follow an unpopular method.

Daniel recites the standard reasons for following the standard method, and which is correct-ish, except that you have to first prioritize the objective vs. the popular. It's okay to be unpopular and right. But it is a really bad idea to be unpopular and wrong.

Traditional is not intrinsically better than innovative, nor is the opposite better. What is better is – the correct. What you should be interested in is a demonstration that your conclusion is correct. Scientists ignore arbitrary conjectures, and they pay attention to conclusions that are supported by an integration of reason and observation. What reason can you give to support the claim that this root is "phonosemantic". Where are the observations, and what is the logic that connects those observations to the phonosemantic conclusion?

[FlatAssembler]

An "established methodology" should be used until it is proven that an alternative methodology gives better results.

Mainstream methodology in toponymy gives no p-values (which is what is meant by "evidence" in hard sciences). My methodology gives some p-values (in the case described in my text about the river name Karašica, the p-value is somewhere between 1/300 and 1/17, depending on the assumptions you make about the collision entropy of the Croatian language). Therefore, my methodology gives results that somebody who follows the scientific method would prefer.

[Daniel]

Statistics are consistently used in linguistics when working with a representative sample. Etymology is not generally thought of in this way, because individual words are historical accidents, not representative samples (there's just one data point), so we can't reliably generalize. Statistics are used more generally to compare languages, e.g. to see if they are related (where the sample is many words, not just one), but even then it still is controversial and unclear to what degree such an approach (e.g. a "big data" method) works better than the traditional work "by hand" by experts looking at details of etymology and intuitive plausibility of connections, etc.

A p-value is not a desirable thing in science, nor required for the "scientific method". It's just one tool available to scientists, which can be used when appropriate. By the way, a p-value should not be "between 1/300 and 1/17". It should have a precise value, which is either higher or lower than the arbitrarily-selected cutoff point. So you might select .05 as the cutoff, and if your p-value is less than that, you consider the result to be significant (i.e. unlikely to observe that distribution by chance), and you report simply "p-value less than .05". You can also include other kinds of statistics, such as a confidence interval (that's what "between 1/300 and 1/17" sounds like), but that's something else. Regardless, there has been a huge amount of discussion recently about the general unreliability of p-values in research, i.e. researchers saying "this result is statistically significant", because although the numbers are objectively calculated, the methodology for gathering the data and deciding what it represents is not. Replicability is a neglected area of science, and in general a number of recent papers have found something along the lines of "most published conclusions are wrong", specifically in the case of experiments trying to make statistical generalizations.

In short, dismissing traditional insights into the field while hiding your methodology behind a shiny "p-value" isn't going to make it any more correct. It all boils down to the methodology, and whether your assumptions and interpretations of the data are correct.

"Big data" approaches to historical linguistics run into this problem: the idea is that if you feed enough data into a computer, eventually the calculated result will be meaningful. But it turns out that the assumptions build into the models, and lack of respect for traditional understanding of how these things works, simply leads to unreliable results. Here's a great Youtube video of a lecture about that: https://youtu.be/4jHsy4xeuoQ

Innovation in science is crucial. But only when it's actually an improvement, and generally after building on a solid foundation of existing methods.