DigitalResources Electronic Working Paper 2016-001 New perspectives on the genetic classification of Manda (Bantu N.11) Hazel Gray and Tim Roth New perspectives on the genetic classification of Manda (Bantu N.11) Hazel Gray and Tim Roth SIL International® 2016 SIL Electronic Working Paper 2016-001 ©2016 SIL International® ISSN 1087-9250 Fair Use Policy Documents published in the Electronic Working Paper series are intended for scholarly research and educational use. You may make copies of these publications for research or instructional purposes (under fair use guidelines) free of charge and without further permission. Republication or commercial use of an Electronic Working Paper or the documents contained therein is expressly prohibited without the written consent of the copyright holder(s). Managing Editor Eric Kindberg Series Editor Lana Martens Content/Copy Editor Mary Huttar Compositor Bonnie Waswick Abstract Manda (N.11) is an under-documented Bantu language in southwestern Tanzania, with most mention of its closest genetic affiliation in the work of Nurse (1988). Nurse concludes that Manda belongs with the Southern Tanzania Highlands (SH) subgroup based primarily on phonological evidence. This paper uses new data from workshops and surveys conducted by SIL International to show that Nurse’s conclusion does not take into account the necessary dialectal information, namely that the Matumba dialect (which Nurse uses) is phonologically distinct from the remaining Manda dialects. Lexicostatistical, phonological, and sociohistorical evidence is taken into account. Further, in light of this new evidence, we propose two likely historical scenarios, both of which posit that Manda is most closely genetically affiliated with the Rufiji subgroup. Contents 1 Introduction and background 2 Dialectometry and lexicostatistical evidence 3 Phonological evidence 3.1 Dahl’s Law 3.2 Spirant weakening 3.3 *NC>̥ NC or N 4 Sociohistorical evidence 5 Synthesis and conclusion Appendix A: Lexicostatistics Appendix B: 296-item wordlist for corpus languages References iv 1 Introduction and background Manda [ISO 639-3 code: mgs] is a Bantu language (N.11) spoken by the Manda and Matumba language communities located in the area between Lake Nyasa and the Livingstone Mountains (Maho 2009). The language area straddles two administrative regions in Tanzania: Njombe Region, north of the Ruhuhu River, and Ruvuma Region, south of the river. The area is bordered to the north by Kisi (G.67),1 to the east by Pangwa (G.64) and Ngoni (N.12), and to the south by Matengo (N.13) and Mpoto (N.14) (Maho 2009). Lewis et al. (2015) report the Manda (and Matumba) population at 22,000. A previous SIL survey puts the estimate even higher, between 25,000 and 40,000 (Anderson et al. 2003a). This paper uses survey data from four other locations in addition to the Matumba variety in Luilo: Iwela, Lituhi, Litumba Kuhamba and Nsungu (see map below). We examine three streams of evidence (lexicostatistical, phonological, and sociohistorical) in this study to determine the closest genetic relatives of Manda (and Matumba). New data is put forward from survey work conducted by SIL personnel in 2013 and subsequent additional linguistic research (Gray, forthcoming; Gray and Mitterhoffer 2016). 1 The Guthrie codes for Bantu are referential, reflecting geography and not genetic relationship (see Schadeberg 2003: 146). 1 2 3 The Matumba consider themselves a separate ethnic group from the Manda, but still regard their language to be essentially the same as Manda. The Matumba themselves claim that they were once Manda who moved from the shores of Lake Malawi up into the mountains (Anderson et al. 2003a). The prestige dialect (even according to the Matumba) of Manda is spoken in the area near Ilela and Nsungu, villages on the lakeshore (Gray and Mitterhoffer 2016). Various comparative linguistic studies have included Manda wordlists (Guthrie 1971, Nurse and Philippson 1975) and mention of Manda is made in diachronic studies by Nurse and Philippson (1980) and Nurse (1988, 1999). None of these studies mention the Matumba, so it is quite likely that the Matumba were unintentionally grouped with the Manda in previous studies. As we will see in section 3, this lack of previous dialect research has given rise to some misconceptions about the innovations that Manda shares with its neighbors. Of those who have studied the Manda language with the aim of positing its closest genetic affiliation, Nurse and Philippson (1980) and Nurse (1988, 1999) are in conflict with Ehret (1999, 2009). Ehret (2009:17) puts Manda alongside Ngoni in the Rufiji-Ruvuma (RR) subgroup, whereas Nurse classifies Manda within his Southern (Tanzania) Highlands (SH) subgroup. These are the main hypotheses we evaluate in light of the new data which reflects a better understanding of Manda dialectology. RR consists of two sub-branches. We are concerned primarily with Rufiji, which includes Manda’s immediate neighbors: Ngoni, Matengo, and Mpoto. The SH subgroup includes the G.60 languages, of which we are primarily concerned with Kisi and Pangwa for the same reason. This paper mainly focuses on the arguments put forward by Nurse (1988), since he deals with the question of Manda’s genetic affiliation in the most depth. Ehret primarily relies on stem-morpheme innovations (lexical/semantic evidence) in his (1999) work, and does not offer the same depth of interaction with the corpus most like an SH language that Nurse does. From the Manda data Nurse uses, Manda appears to behave phonologically mostly like an SH language. However, we argue that the Manda data Nurse uses appears to be the Matumba dialect, which phonologically is quite different from the other Manda dialects. In section 3 we see how the features of Dahl’s Law, spirant weakening, and NC̥>NC or N cast doubt on Nurse’s argument for Manda as SH. We offer three scenarios regarding the genetic history of Manda and Matumba in section 5. In section 2 we present initial lexicostatistical evidence using dialectometry. Manda and Matumba varieties are compared to the other corpus languages: Kisi, Matengo, Mpoto, Ngoni, and Pangwa. Section 3 examines the phonological evidence for the corpus languages, while section 4 briefly examines the sociohistorical evidence. Section 5 concludes the paper with a synthesis, preliminary conclusions, and possibilities for future research. 2 Dialectometry and lexicostatistical evidence Dialectometry is essentially quantitative dialectology. Distance-based networks are examples of such quantitative data explorations. A distance-based network analysis offers ‘‘an introductory visual means of data exploration’’ (Pelkey 2011:279). Subsumed under the rising field of dialectometry are several distance-based algorithmic applications that aim to help researchers explore language variation and/or change, while “making it possible to show more than one evolutionary pathway on a single graph” (Holden and Gray 2006:24). To create a distance-based network the opposite values of regular lexicostatistical percentages are used within a standard matrix (e.g., the Kisi and Pangwa languages in figure 2 are 0.59 similar, but 0.41 dissimilar; see Appendix A). The resulting distance matrix is then subjected to the Neighbor-Net algorithm, as developed by Bryant and Moulton (2004) and implemented within the Splits Tree 4 (4.11.3) software program (see Huson and Bryant 2010). If the lexical relationships are ambiguous, the length of each branch indicates the confidence level of the split. Figure 1 shows such a network using four Bantu lects from southwest Tanzania (Roth 2011:43). 4 Nyika Nyiha Safwa Malila Figure 1. Sample network demonstrating ambiguity (adapted from Roth 2011:43). In figure 1, the middle box indicates the ambiguous relationship: Split A—Nyika and Nyiha/ Safwa and Malila versus Split B—Nyika and Safwa/ Nyiha and Malila. In figure 1, Split A is more likely. Holden and Gray discuss other patterns and their meaning within the network diagram: Rapid radiation may be inferred from a lack of phylogenetic signal, i.e. a rake- or star-shaped phylogeny, whereas reticulation would indicate possible borrowing. Reticulations can also pinpoint those languages which may have been involved in borrowing. Complex chains of conflicting relationships involving numerous languages may indicate that borrowing occurred in the context of dialect chains. (2006:24) If the lexical relationships are more clear, the splits-graph looks more like a regular tree diagram (see Holden and Gray (2006) for further explanation of the Neighbor-Net algorithm, and the unique historical relationships between other Bantu languages). Figure 2 below is based on the lexicostatistical data in Appendix A. The data includes lexical percentages from 313-item wordlists elicited in five locations (Iwela, Lituhi, Litumba Kuhamba, Luilo and Nsungu) during the 2013 dialect survey (Gray and Mitterhoffer 2016). This 313-item wordlist was based on the 100-item Leipzig-Jakarta wordlist (Tadmor 2009). Two hundred ninety-six of the lexical items2 in the 313-item wordlist were compared to data from SIL Fieldworks Language Explorer (FLEx) 2 Some lexical items were omitted due to duplications in the data. 5 databases for Kisi and Pangwa, and CBOLD data for Mpoto, Matengo and Ngoni (supplemented by data from Ngonyani 2003 and Yoneda 2006) using the comparative method as the basis for determining cognacy. The lexical data (the 296-item wordlist) can be found in Appendix B. Consider the distance- based network below in Figure 2. Matengo Pangwa Kisi RR SH Mpoto Ngoni Lituhi Litumba Kuhamba Nsungu Luilo Iwela (Matumba) Manda Figure 2. Distance-based network for SH, Rufiji and Manda corpus languages. From the diagram in figure 2, we can clearly see the split between the branch containing the SH languages (Pangwa and Kisi) on the left and two of the Rufiji languages (Matengo and Mpoto) on the right. We can also see that the Manda dialects, while lexically related to SH and Rufiji, are at the same time lexically distinct, i.e., the Manda dialects seem to have a split-lexicon.