Slow rate of lexical replacement and deeper genetic relationships Jean-Marie Hombert Rebecca Grollemund Gérard Philippson Berlin, Feb 22, 2010

Speed of lexical replacement 20% of change in basic vocabulary/1000 years Percentages of cognates After 1.000 years : 64% After 2.000 years : 41% After 10.000 years : 1% Very little hope for detecting deep linguistic relationships between 2 languages

Stability of lexical items Variable rate of change Use of basic vocabulary Variable rate of change in basic vocabulary See Pagel (2000) in Time depth in Historical Linguistics (189-207) Renfrew, MacMahon and Trask : distribution of word rates rather than single rate. This distribution has a long tail (ie very slowly evolving words)

Resistant lexical items IE : 87 languages, Swadesh 200 wordlist One to 46 cognates/meaning Slow changing items : five, I, one, two, who Frequency play a major role : frequently used words evolve at slower rates Pagel, Atkinson and Meade (2007), Nature See Pagel, Atkinson and Meade (2007), Nature Direct estimates of rates of cognate replacement on linguistic phylogenies (family trees) of IE and Bantu languages using a statistical model of word evolution in a bayesian Markov Chain Monte Carlo (MCMC) framework. Rates of cognate replacement for diffrent meanings in IE were correlated with their paired meanings in Bantu (voir Pagel and Meade in Phylogenetic methods.. Ed by Clackson, Forster and Renfrew (2006)

From Pagel et al (2007) Nature; Swadesh 200 word list From Pagel et al (2007) Nature; Swadesh 200 word list. Conjunctions (grey), prepositions (turquoise), adjectives (red), verbs (blue), nouns (green), special adverbs (yellow), pronouns (orange), numbers (purple)

Rank Item Category 1 FIVE Number I Pronoun THREE TWO WHO 6 FOUR ONE WE 9 HOW Adv. 10 NAME Noun TONGUE 12 NEW Adj. WHAT 14 EAR NIGHT THOU 17 TO GIVE Verb NOT STAR TOOTH (FRONT) WHERE Rank Item Category 22 TO DIE Verb EYE Noun HAND SUN WATER Adj. 27 FATHER Pronoun 28 DAY (NOT NIGHT) TO LIVE MOTHER SALT WHEN Adv. 33 FISH HE TO SIT SMOKE SNOW 38 TO DRINK FOOT IN Prep. LONG LOUSE 43 BONE Data from Pagel et al Nature 2007; Estimation of rates of lexical evolution of items from Swadesh 200 word list in 87 IE languages. Number of cognates varied from 1 to 46. Calculations show 100 fold ratio. Numbers, Pronouns and special verbs evolve more slowly. Conjounctions, prepositions and adjectives evolve faster. Numbers are very stable in this list but this is certainly language family specific (IE); then comes pronoms I, we, who..

Loanword Typology Project 41 languages, 1460 meanings Previous studies (Pagel, Holman) were based on Swadesh’s list (ie on a constraint list based on Swadesh’s decision – without any quantitative data to construct the list. Consequently a study based on a much larger lexicon could allow to « construct » a less biased list

From Tadmor, Haspelmath and Taylor « Borrowability and the notion of Basic vocabulary Nouns are borrowed much more often than verbs and adjectives. Content words are borrowed much more often than function words. Resistance to borrowability does not correlate very well with Holman’s list of stable items in Swadesh’s list

From Tadmor, Haspelmath and Taylor « Borrowability and the notion of Basic vocabulary ». The Leipzig-Jakarta word list : This list takes into account not only resitance to borrowability but also the representation rate (existence of meanings having counterparts in the data), analazability (words with complex counterparts) and age of words. Comparison with Swadesh list : 62 items overlap

From Tadmor, Haspelmath and Taylor « Borrowability and the notion of Basic vocabulary ».

Major Bantu subdivisions (from lexico-statistical data, Bastin and Piron 1999)

Bantu languages of Gabon 150 words Algab project

Meaning Leipzig-Jakarta Algab Nb of roots fire 1 45 6 nose 2 35 5 to go 3   water 4 mouth 22 tongue bone 7 blood (root, small) 9 root (big) 2SG pronoun to come 11 breast 12 (breast, chest) rain 13 1SG pronoun 14 louse 15 name wing 17 flesh/meat 18 Meaning Leipzig-Jakarta Algab Nb of roots arm/hand 19 9 3 night 20 61 8 fly   ear 22 neck 23 45 6 far to do/make 25 house 26 4 stone/rock 27 tooth 28 to say bitter hair 31 one 32 big 35 5 who? 34 3SG pronoun to hit/beat 36 leg/foot 37 68 10 fish 38 2

Conclusion Not convinced… BUT Need comparable data from different linguistic zones in Africa Could be interesting for areal studies

Thank you

Holman et al (2008) Item 1. louse 2. two 3. water 4. ear 5. die 6. I 7. liver 8. eye 9. hand 10. hear 11. tree 12. fish 13. name 14. stone 15. tooth 16. breasts 17. you 18. path 19. bone 20. tongue Holman et al (2008) Item 21. skin 22. night 23. leaf 24. rain 25. kill 26. blood 27. horn 28. person 29. knee 30. one 31. nose 32. full 33. come 34. star 35. mountain 36. fire 37. we 38. drink 39. see 40. bark 41. new 42. dog 43. sun Holman et al 2008 Rank of Stability of first 40 lexical items from Swadesh list Stability measured for 100 Swadesh list by considering 245 languages (from 63 different language families) This study allows us to avoid family specific bias (ie numbers very present in Pagel et al’s list in IE have disappeared here

From Holman et al « Explorattions in automated language classification »