Input vs. network effects in the multiagent modeling of morphological leveling in Old Castilian

1. Input vs. network effects in the multiagent modeling of morphological leveling in Old Castilian Harry Howard Tulane University LASSO 2006 Laredo, TX

2. Tuten (2003) on koineization in the history of Spanish • By the 11th century, (southern) Castilian differed strikingly from its Romance neighbors in the simplicity of its definite articles • Castilian had almost reached its modern analyticity, with no allomorphs of the plural forms and only two preposition + article contractions (al, del). • The only difference was allomorphy in the singular forms (el-elo; la-ela-l). In contrast, the other Ibero-Romance dialects were considerably more complicated, with multiple article allomorphs, as well as contractions onto the prepositions por, de, a, con, and en. Harry Howard

3. Koineization • Tuten attributes the simplicity of Castilian to koineization, and in particular to a process of dialect leveling that occurs when speakers leave established, monodialectal social networks whose members are bound together by strong ties and move into new, polydialectal social networks whose members are bound together only weakly. • In the particular case of 11th century Castilian, Tuten see the initial stages of the Reconquest and the establishment of Burgos as the capital of its leading edge as supplying the conditions for the latter kind of society. Harry Howard

4. Our response • Tuten’s updating of a classic problem in Romance linguistics, conflates two causal factors, • how language is learned in situations of multiple competing inputs (i.e. dialect mixing) • how language is learned in situations of social innovation (i.e. weak social networks). • Of course, there are no longer any native speakers of 11th century Castilian to interview, so Tuten cannot be faulted too harshly for not disentangling his causal factors more carefully. Harry Howard

5. Our approach • In fact, the lack of real native speakers means that the best we can do is construct artificial ones, via computer programs, and see how they behave as parameters are varied. • This brings us to the realm of multiagent modeling, which has recently seen a burst of enthusiasm in the creation of sociolinguistic microcosms for the simulation of language evolution. • De Boer’s (2001) investigation of the evolution of vowel systems provides a convenient starting point. Harry Howard

6. Table 1. Definite article allomorphs in Galicia & Portugal Harry Howard

7. The Western Mediterranean in 1030 Harry Howard

8. The algorithm • an agent chooses a meaning from its semantic memory. In our simulations, this will be an unexpressed noun with features for gender and number, plus a preceding context, either one of the five prepositions or not. • the phonemic representation of the meaning is retrieved from memory, converted to phonetic form, and ‘spoken’ to another agent, which • matches it to its phonemic memory, in order to • retrieve a meaning which • it tries to match against the meaning intended by the speaking agent. If there is a match, • the hearing agent stores the phonemic-semantic association. Harry Howard

9. Table 2. Vectors for the gender and number features of Ibero-Romance nouns Harry Howard

10. Table 3. Vectors for Ibero-Romance free and prepositional contexts of article allomorphs Harry Howard

11. (1) Phonemes for Ibero-Romance definite article allomorphs • vowels: /(i), e, a, o, u/ • consonants: /k, d, s, n, l, r, p/ Harry Howard

12. (2) Hubey’s (1999) three dimensional phase space of acoustic-articulatory events • x) stricture quality, the area (length*width) of a stricture multiplied by its characteristic frequency ω measured in radians/sec = l*w*ω. • y) stricture change, the time derivative of the change in stricture area = d/dt (l*w)*ω. • z) quasi-Reynold’s number, found by multiplying the characteristic length (K) by velocity (v = l /time) = K*v. Harry Howard

13. (4) Hubey’s approximations • x) stricture quality = {{k,g,x,h}, r, {l,s,z}, {d,t,}, {f,v}, {p,b,m}} • y) stricture change = {{vowels}, {dipthongs}, {r,l,m.n,s,f,,x,h}, {b,d,g}, {p,t,k}} • z) Reynold’s number = {{vowels, dipthongs}, {r,l,m,n}, {v,z}, {s,f,,x,h}} Harry Howard

14. Table 4. Phonemic vectors for the Ibero-Romance definite article allomorphs Harry Howard

15. Table 5. Word matrix for Galician-Portuguese pola Harry Howard

16. Figure 1. Fifteen [l], made by adding noise with mean 0 and standard deviation 1 to /l/ Harry Howard

17. Figure 2. Frequency of Galician-Portuguese morphemes idealized at 1:3:5 Harry Howard

18. Figure 3. Development of Galician-Portuguese morpheme categories towards 1:3:5 Harry Howard

19. Figure 4. Imperfect development of Galician-Portuguese morpheme categories Harry Howard

20. Production • A simple algorithm for leveling the preposition-article contractions: • Use more frequent forms over less frequent ones • Note that the less frequent forms will be even less frequent in the environment of 13th century Castilian, since there were also competing forms from Leonese, and Aragonese, as well as Northern Castile Harry Howard

21. The social model • It appears that strong ties/dense social networks are necessary to maintain less frequent forms, but it could also be that such societies are more isolated or less porous to outsiders Harry Howard