Glottochronology (from Attic Greek γλῶττα 'tongue, language' and χρόνος 'time') is the part of lexicostatistics which involves comparative linguistics and deals with the chronological relationship between languages.Sheila Embleton (1992). Historical Linguistics: Mathematical concepts. In W. Bright (Ed.), International Encyclopedia of Linguistics
The idea was developed by Morris Swadesh in the 1950s in his article on Salish internal relationships. He developed the idea under two assumptions: there indeed exists a relatively stable basic vocabulary (referred to as ) in all languages of the world; and, any replacements happen in a way analogous to radioactive decay in a constant percentage per time elapsed. Using mathematics and statistics, Swadesh developed an equation to determine when languages separated and give an approximate time of when the separation occurred. His methods aimed to aid linguistic anthropologists by giving them a definitive way to determine a separation date between two languages. The formula provides an approximate number of centuries since two languages were supposed to have separated from a singular common ancestor. His methods also purported to provide information on when ancient languages may have existed.
Despite multiple studies and literature containing the information of glottochronology, it is not widely used today and is surrounded with controversy. Glottochronology tracks language separation from thousands of years ago but many linguists are skeptical of the concept because it is more of a 'probability' rather than a 'certainty.' On the other hand, some linguists may say that glottochronology is gaining traction because of its relatedness to archaeological dates. Glottochronology is not as accurate as archaeological data, but some linguists still believe that it can provide a solid estimate.
Over time many different extensions of the Swadesh method evolved; however, Swadesh's original method is so well known that 'glottochronology' is usually associated with him.Holm, Hans J. (2007). The new Arboretum of Indo-European 'Trees'; Can new algorithms reveal the Phylogeny and even Prehistory of IE?. Journal of Quantitative Linguistics 14-2:167–214
Lists were compiled by Morris Swadesh and assumed to be resistant against borrowing (originally designed in 1952 as a list of 200 items, but the refined 100-word list in Swadesh (1955)Swadesh, Morris. (1955). Towards greater accuracy in lexicostatistic dating. International Journal of American Linguistics, 21, 121–137 is much more common among modern day linguists).
The core vocabulary was designed to encompass concepts common to every human language such as personal pronouns, body parts, heavenly bodies and living beings, verbs of basic actions, numerals, basic adjectives, kin terms, and natural occurrences and events. Through a basic word list, one eliminates concepts that are specific to a particular culture or time period. It has been found through differentiating word lists that the ideal is really impossible and that the meaning set may need to be tailored to the languages being compared. Word lists are not homogenous throughout studies and they are often changed and designed to suit both languages being studied. Linguists find that it is difficult to find a word list where all words used are culturally unbiased. Many alternative word lists have been compiled by other linguists and often use fewer meaning slots.
The percentage of (words with a common origin) in the word lists is then measured. The larger the percentage of cognates, the more recently the two languages being compared are presumed to have separated.
American Linguist Robert Lees obtained a value for the "glottochronological constant" ( r) of words by considering the known changes in 13 pairs of languages using the 200 word list. He obtained a value of 0.8048 ± 0.0176 with 90% confidence. For his 100-word list Swadesh obtained a value of 0.86, the higher value reflecting the elimination of semantically unstable words.
t = a given period of time from one stage of the language to another (measured in millennia),
By testing historically verifiable cases in which t is known by nonlinguistic data (such as the approximate distance from Classical Latin to modern Romance languages), Swadesh arrived at the empirical value of approximately 0.14 for L, ( c?) which means that the rate of replacement constitutes around 14 words from the 100-wordlist per millennium. This is represented in the table below.
For Amerind, correlations have been obtained with radiocarbon dating and blood groups as well as archaeology.
Glottochronology has been controversial ever since, partly because of issues of accuracy but also because of the question of whether its basis is sound (for example, Bergsland 1958; Bergsland and Vogt 1962; Fodor 1961; Chrétien 1962; Guy 1980). The concerns have been addressed by Dobson et al. (1972), Dyen (1973)Dyen, Isidore, ed. (1973). Lexicostatistics in genetic linguistics: Proceedings of the Yale conference, April 3–4, 1971. La Haye: Mouton. and Kruskal, Dyen and Black (1973).Some Results From the Vocabulary Method of Reconstructing Language Trees, Joseph B. Kruskal, Isidore Dyen and Paul Black, Lexicostatistics in Genetic Linguistics, Isidore Dyen (editor), Mouton, The Hague, 1973, pp. 30–55 The assumption of a single-word replacement rate can distort the divergence-time estimate when borrowed words are included (Thomason and Kaufman 1988).
The presentations vary from "Why linguists don't do dates" to the one by Sergei Starostin discussed below. Since its original inception, glottochronology has been rejected by many linguists, mostly Indo-Europeanists of the school of the traditional comparative method. Criticisms have been answered in particular around three points of discussion:
Brainard (1970) allowed for chance cognation, and drift effects were introduced by Gleason (1959). Sankoff (1973) suggested introducing a borrowing parameter and allowed synonyms.
A combination of the various improvements is given in Sankoff's "Fully Parameterised Lexicostatistics". In 1972, Sankoff in a biological context developed a model of genetic divergence of populations. Embleton (1981) derives a simplified version of that in a linguistic context. She carries out a number of simulations using this which are shown to give good results.
Improvements in statistical methodology related to a completely different branch of science, phylogenetics; the study of changes in DNA over time sparked a recent renewed interest. The new methods are more robust than the earlier ones because they calibrate points on the tree with known historical events and smooth the rates of change across them. As such, they no longer require the assumption of a constant rate of change ( Gray & Atkinson 2003).
The resulting formula, taking into account both the time dependence and the individual stability quotients, looks as follows:
In that formula, − Lc reflects the gradual slowing down of the replacement process because of different individual rates since the least stable elements are the first and the quickest to be replaced, and the square root represents the reverse trend, the acceleration of replacement as items in the original wordlist "age" and become more prone to shifting their meaning. This formula is obviously more complicated than Swadesh's original one, but, it yields, as shown by Starostin, more credible results than the former and more or less agrees with all the cases of language separation that can be confirmed by historical knowledge. On the other hand, it shows that glottochronology can really be used only as a serious scientific tool on language families whose historical phonology has been meticulously elaborated (at least to the point of being able to distinguish between cognates and loanwords clearly).
Methodology
Glottochronologic constant
Divergence time
+ Glottochronology Time Scale 86% 74% 64% 55% 47% 40% 30% 22% 16% 12% 9% 7% 5%
Results
Example Wordlist
+Glottochronological Turkish 100 Word List hep (all) ateş (fire) boyun (neck) bu (that) kül (ashes) balık (fish) yeni (new) şu (this) kabuk (bark) uçmak (fly) gece (night) sen (thou) karın (belly) ayak (foot) burun (nose) dil (tongue) büyük (big) vermek (give) bir (one) diş (tooth) kuş (bird) iyi (good) kişi (person) ağaç (tree) ısırmak (bite) yeşil (green) yağmur (rain) iki (two) kara (black) saç (hair) kızıl (red) yürümek (walk) kan (blood) el (hand) yol (road) sıcak (warm) kemik (bone) baş (head) kök (root) su (water) yakmak (burn) duymak (hear) kum (sand) biz (we) bulut (cloud) gönül (heart) demek (say) ne (what) soğuk (cold) ben (I) görmek (see) beyaz (white) gelmek (come) öldürmek (kill) tohum (seed) kim (who) ölmek (die) bilmek (know) oturmak (sit) kadın (woman) köpek (dog) yaprak (leaf) deri (skin) sarı (yellow) içmek (drink) yalan (lie) uyumak (sleep) uzun (long) kuru (dry) ciğer (liver) küçük (small) yok (not) kulak (ear) bit (louse) duman (smoke) göğüş (breast) yer (earth) erkek (man-male) ayaktakalmak (stand) hayvan tırnagı (claw) yemek (eat) çok (many) yıldız (star) dolu (full) yumurta (egg) et (meat-flesh) taş (stone) boynuz (horn) göz (eye) dağ (mountain) güneş (sun) diz (knee) yağ (fat-grease) ağız (mouth) yüzmek (swim) ay (moon) tüy (feather) isim (name) kuyruk (tail) yuvarlak (round)
Discussion
Modifications
Starostin's method
See also
Bibliography
External links
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