[Lingtyp] Reporting cross-linguistic frequencies

[JOO Ian]

Dear Omri,

I agree that statements like “n% of the world’s languages are x” are potentially misleading.
Not only for the non-independence reason you’ve mentioned, but also the fact that languages (lects) are not really countable, but rather gradient variables.
For example – How many Chinese languages are there? Well, according to Glottolog, it says 30 – but is “Wu Chinese” really a language when the Wu branch itself consists of many distinct, non-intelligible varieties? Are there then 300 Chinese languages? Or 3000?
So it’s not very helpful to start with the presupposition that there exist a certain fixed number of languages in the world.

Regards,
Ian

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朱　易安
JOO, IAN
准教授
Associate Professor
小樽商科大学
Otaru University of Commerce

🌐 ianjoo.github.io<http://ianjoo.github.io/>
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보낸 사람: Lingtyp <lingtyp-bounces at listserv.linguistlist.org>이(가) 다음 사람 대신 보냄: Omri Amiraz via Lingtyp <lingtyp at listserv.linguistlist.org>
날짜: 화요일, 2025년 11월 18일 18:25
받는 사람: lingtyp at listserv.linguistlist.org <lingtyp at listserv.linguistlist.org>
주제: [Lingtyp] Reporting cross-linguistic frequencies
Dear Colleagues,
I would like to raise the question of how cross-linguistic frequencies of typological features ought to be reported. The issue has been discussed extensively, but I still find some aspects conceptually confusing, so I hope this discussion might be helpful for others as well.
To make this concrete, consider the order of object and verb (OV, VO, no dominant order). Suppose, for the sake of argument, that we have complete data for every language in Glottolog. This would give us the actual proportion of languages that are OV vs. VO in the present-day world. The core problem, however, is that languages are not independent datapoints, so these actual frequencies also reflect genealogical and areal biases.
For that reason, it is common practice to report adjusted frequencies instead, either through non-proportional stratified sampling (Dryer 2018) or through statistical bias controls (Becker & Guzmán Naranjo 2025). As far as I understand, both methods aim to estimate something like: If each language were independent (as if every language were an isolate and had no contact with its neighbors), what proportion would be OV vs. VO? In other words, the population being described is not the set of existing languages but a hypothetical (and unrealistic) set of independent languages.
Now, suppose that the actual frequencies of OV and VO are equal, but the adjusted frequency of OV is higher. In that case, it feels counterintuitive to say that OV is more common cross-linguistically than VO. Perhaps it is clearer to speak in terms of probabilities rather than proportions, given that the population is hypothetical. For instance, we might say: “When genealogical and areal biases are controlled for, the probability of a language being OV is 0.6". This means that the chance that a randomly sampled language isolate with no contact would be OV is 0.6. By contrast, saying “60% of the world’s languages are OV” when referring to an adjusted frequency seems potentially misleading.
I would appreciate hearing what others in the community think about how such statistics should ideally be reported.
Best regards,
Omri

References:
Becker, Laura and Guzmán Naranjo Matías. 2025. Replication and methodological robustness in quantitative typology. Linguistic Typology.
Dryer, Matthew S. 2018. On the order of demonstrative, numeral, adjective, and noun. Language 94(4), 798-833.
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