Volume 14 Issue 1 (2016) DOI:10.1349/PS1.1537-0852.A.468 Note: Linguistic Discovery uses Unicode characters to represent phonetic symbols. Please see Optimizing Display for requirements to accurately reproduce this page. Exploring grammatical complexity crosslinguistically: The case of gender Francesca Di Garbo University of Helsinki This paper proposes a set of principles and methodologies for the crosslinguistic investigation of grammatical complexity and applies them to the in-depth study of one grammatical domain, gender.
The complexity of gender
is modeled on the basis of crosslinguistically documented properties of gender systems and by taking into consideration interactions between gender
and two other grammatical domains: nominal number and evaluative morphology. The study proposes a complexity metric for gender that consists
of six features: “Gender values”, “Assignment rules”, “Number of indexation (agreement) domains”, “Cumulative exponence of gender and number”, “Manipulation of gender assignment triggered by number/countability”, and “Manipulation of gender assignment triggered by size”. The metric
is tested on a sample of 84 African languages, organized in subsamples of genealogically related languages. The results of the investigation show that: (1) the gender
systems of the sampled languages
lean towards high complexity scores; (2) languages with purely semantic
gender assignment tend to lack pervasive
gender indexation; (3) languages with a high number of gender distinctions tend to exhibit pervasive
gender indexation; (4) some of the uses of manipulable gender assignment are only attested in languages with a high number of gender distinctions and/or pervasive
indexation. With respect to the distribution of the gender
complexity scores, the results show that genealogically related languages tend to have the same or similar
gender complexity scores. Languages
that display exceedingly low or high gender complexity scores when compared
with closely related languages exhibit distinctive sociolinguistic profiles (contact,
bi- or multilingualism). The implications of these findings
for the typology
of gender systems
and the crosslinguistic study of grammatical complexity and its distribution are discussed. 1. Introduction Investigating the complexity of individual grammatical domains from a crosslinguistic perspective is still a novel research area within language
typology. This paper focuses on the empirical
study of grammatical complexity and proposes a set of principles and methodologies that can be operationalized to explore
linguistic complexity crosslinguistically.[1] The
paper takes inspiration from the suggestions made by Miestamo (2006b, 2008) on the typological study of grammatical complexity. According to Miestamo, complexity metrics suitable
for typological purposes should
not aim to assess the grammatical complexity of languages in their entirety (global complexity), but rather focus on specific
domains of grammar (e.g. functional domains)
as encoded across
languages, and attempt
to characterize “the cross-linguistic variety in the complexity of each functional domain and the interactions between domains”
(2006b) (local complexity). The grammatical domain that I investigate in this paper
is grammatical gender. Gender is
a type of nominal classification device (in the sense of Aikhenvald 2003) that is commonly associated with high degrees of complexity, inasmuch as it presupposes inflectional morphology (agreement) and rather
opaque grammaticalization
paths (Corbett 1991; Dahl 2004; Nichols 1992). In this study, I attempt to model the complexity of gender by identifying a set of dimensions that
characterize gender systems
crosslinguistically and by taking into consideration interactions and possible asymmetries between
gender and two other nominal grammatical domains, number and evaluative morphology. The paper proposes a complexity metric for gender. This metric is then tested
on a sample of 84 African languages. The aim of the paper is to investigate whether crosslinguistic variation in the types of gender systems
attested in the sample languages is tied to certain levels of complexity, and why this might be the case. In addition, by exploring
gender complexity within and across genealogical groupings, the study aims to investigate to which extent the complexity of gender – a morphosyntactic feature that is usually conceived of as very stable
in the history of language
families – is conservative across related languages and under which
conditions it is subject to decrease or increase. The paper is structured as follows.
In section 2, I define
the notion of grammatical complexity that I work with. In section
3, I introduce gender as a grammatical domain and consider possible
dimensions for the assessment of gender complexity. The methodology followed in the study is illustrated in section 4: section 4.1 provides an outline of the sampling
procedure; section 4.2 presents the complexity metric and section
4.3 illustrates the method used to compute
complexity scores
for the gender
systems of the sampled languages. The results are presented in section 5 and discussed in section 6, before I provide
some concluding remarks
in section 7. 2. Defining grammatical complexity The idea that all languages are equally complex is known in the literature as the equi-complexity hypothesis and is based
on the assumption that, even though
individual languages may exhibit
different levels of complexity in different
domains of their grammars,
complexity in one domain
is compensated by simplicity in another
domain (complexity trade-offs). The equi-complexity hypothesis has long been maintained as a truism within
linguistic research (for an overview, see McWhorter 2001; Kusters 2003). During the past fifteen
years, however, starting from the comparative study of grammatical complexity in creole and non-creole languages by McWhorter (2001), a whole body of research (see, among others, Dahl 2004; Kusters 2003; Miestamo 2006b; Miestamo et al. 2008; Sinnema¨ki 2011) has suggested that the equi-complexity hypothesis is difficult to
test empirically and that, when tested (e.g., by McWhorter 2001), it is actually problematic to maintain. In a nutshell, this research has shown that “there
is no principled reason
why all languages should be equal in their overall complexity or why complexity in one grammatical area should be compensated by simplicity in
another” (Miestamo 2006b). Once we acknowledge that human languages
may differ in complexity,[2] and that these differences are worth exploring
for a multifaceted array of purposes
(typological, sociolinguistic, historical, etc.), three major challenges follow: (1) how to define complexity; (2) how big a scope a complexity metric should have for it to be meaningful, and (3) which principles might help to assess complexity differences in one or several domains of grammar. The three issues are discussed
in section 2.1, section 2.2, and section 2.3, respectively. 2.1 Absolute and relative complexity There exist two main approaches to the study of linguistic complexity, the relative and the absolute approach (Miestamo 2008). The relative
approach (also known as user-oriented approach) focuses on the costs and difficulties
in language learning and processing. The absolute approach
(also known as theory-oriented approach) rather views complexity as an objective property
of languages. Within the absolute approach, complexity can be assessed
by measuring the number of distinctions within a system/grammatical domain,
and the length of its description. Both approaches have been used, and argued for, in typologically oriented
literature on grammatical complexity. Kusters (2003), for instance, defines
complexity in terms
of difficulty. In his work on the typology
of verbal inflection, Kusters examines
four genealogically unrelated
sets[3] of closely related languages and investigates how, within each set, languages differ in the complexity of verbal inflection and what type of sociolinguistic and sociohistorical factors may account for these differences. His definition of complexity is based on the difficulties – as documented in the psycholinguistic literature on second language acquisition – that
adults incur when learning a new language. According to this definition, languages that are more “adapted” to the presence of L2 learners (exoteric languages, following the terminology proposed by Lupyan & Dale 2010) are less complex than languages that, throughout their history, have not been exposed, or not to the same extent, to the presence of adult learners (esoteric languages, based on Lupyan & Dale 2010). This definition of complexity/difficulty fits well the scope of Kusters’ (2003) study, which is to investigate the effects
of multilingualism, asymmetrical bilingualism
and adult language
contact on language
structures. However,
as Miestamo (2006b) rightly points
out, L2 learners represent only one type of language users. In addition, adult, post-critical threshold language
contact is only one type of contact scenario
in the history of a speech community.[4] It follows that a definition
of complexity/difficulty that is targeted to one category of language users only might
not be inclusive enough if our aim is
to build a more general model of linguistic complexity. Finally, given our still limited
knowledge of the cognitive processes behind language learning
and usage, we do not have enough evidence to model the whole range of difficulties and costs that both L1 and L2 speakers and listeners experience when using language. Thus, based on our current
state of knowledge, the absolute approach allows for a more
general, objective, definition of the notion of complexity. This is in turn essential
for the sake of crosslinguistic comparison. In addition, the absolute approach to grammatical complexity is the one that is more easily connectable with how complexity is
approached by other disciplines (e.g., philosophy, information theory) and thus “opens possibilities for interdisciplinary research” (Miestamo 2008: 27). Advocates of the absolute approach to the typological study of grammatical complexity are, among others, McWhorter (2001); Dahl (2004); Miestamo (2006b, 2008); Nichols (2009); Sinnema¨ki (2011). The absolute approach is followed in this paper. Accordingly, I use the term complexity to refer to absolute complexity and the term difficulty to refer to relative complexity. 2.2 Global vs. local complexity One issue that has been at the center of the recent debate on grammatical complexity is how big a scope a complexity metric should have for it to be meaningful. McWhorter (2001) elaborates a complexity metric
that aims to measure overall differences in the grammatical complexity of creole and non-creole languages. The metric captures
phonological, morphological, syntactic
and semantic patterns
that involve various types of redundancy
(in terms of number of overt distinctions and amount of rules) and thus qualify a language as more complex than another.
Two languages
are investigated in the first part of the
study, the highly
inflectional language Tsez (Nakh-Daghestanian) and the creole
language Saramaccan. The metric individuates
clear-cut complexity differences
between the two languages: Sarammaccan systematically qualifies as simpler
than Tsez with respect to all the parameters under investigation. In the second
part of the study, the same complexity metric is used to compare
Saramaccan with an non-creole analytic
language, Lahu (Sino-Tibetan), based on the hypothesis that “the complexity difference between creoles and analytic
languages would be less than that between them and inflected languages” (McWhorter 2001: 143). Nevertheless, the comparison reveals complexity differences between
Saramaccan and Lahu that are similar to those found for Tsez and Saramaccan. These results would seem to confirm McWhorter’s hypothesis whereby the grammar of creole languages is systematically simpler than that of non-creole languages. The question
however remains whether a metric of this type could be effectively used to capture complexity differences (1) between a higher number of languages than those considered in McWhorter’s study, and (2) based on a sampling
procedure that is independent of the creole/non-creole dichotomy. Developing a metric that would satisfy these conditions and would allow us to compute
the total complexity of a language
in typologically meaningful ways is ultimately a massive,
daunting task (see also discussion in Miestamo 2006b, 2008; Nichols 2009). In addition, even if, as suggested by Nichols (2009: 111), one would be able “to draw a representative sample of complexity in enough different
grammatical domains, relatively easy to survey, to
give a reliable indication of whether overall complexity does or does not vary”, it would be still very hard (and probably
even impossible) to establish the mutual comparability between the criteria used in the metric. In other words, it would be extremely difficult to decide whether,
for instance, the number of tense distinctions, phonemes, or gender distinctions that are grammaticalized in a given language
contribute in the same way to the total complexity of that language.
Miestamo (2006b, 2008) refers to this as the problem of comparability and suggests that in view of this difficulty, the crosslinguistic study of grammatical complexity should
be based on individual areas of grammar, such as functional domains, rather than on grammars
in their entirety, and thus have a local rather than global scope. In this paper, I follow this suggestion and investigate the complexity of one grammatical domain, gender. In addition, based on Dahl (2011), I argue that in order to be maximally local, complexity metrics should be based on ceteribus paribus comparisons, that is on statements of the type: “Everything else being equal,
X is more complex
than Y.” 2.3 Complexity
principles In this study, I suggest
that, within an absolute and local approach
to grammatical complexity (see section 2.1 and 2.2), three principles can be used as general guidelines to define the variables of a complexity metric:
the Principle of Fewer Distinctions, the Principle
of One-Meaning–One-Form and
the Principle of Independence. The first two principles are well established in the literature on grammatical complexity (for an overview, see Miestamo 2008). The third principle, the Principle of Independence, was introduced
by Di Garbo (2014) to account for interactions between functional domains
and complexity. In the following, I outline my definitions of the three principles: •The Principle of Fewer Distinctions (proposed by Miestamo 2006a, 2008 and also known as Principle of Economy, see e.g., Kusters 2003):
Everything else being equal, a grammatical domain with n distinctions is less complex
than one with n+1 distinctions. •The Principle
of One-Meaning–One-Form (well established in the literature
on theoretical morphology and linguistic complexity, also known as the Principle
of Transparency, see, for instance,
Kusters 2003): (a) Everything else being equal, a grammatical meaning
with n
forms is less complex
than one with n+1 forms; (b) Everything else being equal, a grammatical form with n meanings is less complex than one with n+1 meanings. •The Principle of Independence (introduced by Di Garbo 2014):[5] Everything else being equal, a grammatical domain that is independent
of semantic and functional properties of other domains is less complex than a grammatical domain that is dependent on n or n+1 semantic and functional properties
of other grammatical domains. The Principle of Fewer Distinctions is concerned with the type and number of grammatical meanings
that a language expresses
within a given domain of grammar. For instance,
other things being equal,
a language with more than five genders (e.g., Swahili) is more complex in this respect than a language with three genders only (e.g.,
German). The Principle
of One-Meaning–One-Form has to do with the type of encoding of a grammatical meaning within a given domain of grammar. The Principle of One-Meaning–One-Form can be operationalized in two ways, depending on whether
we consider the mapping between
form and meaning or, vice versa, the mapping between meaning and form. In addition, as suggested by Miestamo (2008: 33), the relationship between form and meaning can be investigated both at the paradigmatic and syntagmatic level. For instance,
with respect to the encoding of standard negation, Italian, whose standard negator is non, is, other things being equal, less complex than French,
which typically uses a discontinuous marker, ne...pas, to signal standard negation. Or, similarly,
other things being equal, Turkish is simpler than German with respect to the type of exponence of case and number. In Turkish,
the two grammatical meanings
are encoded separately
(one form for each meaning), whereas
in German, number and case are encoded cumulatively (one marker for several meanings).[6] Both these violations of the Principle of One-Meaning–One-Form operate
on the syntagmatic level. On the other hand, phenomena
such as allomorphy and syncretism represent
a violation of the Principle
of One-Meaning–One-Form at the paradigmatic level. Finally, the Principle of Independence models interactions between
domains and their effect on complexity. For instance, a language in which gender
assignment is dependent on evaluative meanings – if, e.g., masculine
nouns can be shifted to the feminine
gender when a diminutive meaning is encoded
(as in the Berber language Kabyle)
– is more complex
in this respect than a language
in which gender assignment cannot be manipulated for such purposes
(as in the Romance language
Italian). In the remainder of this paper, the Principle of Fewer Distinctions, the Principle of One-Meaning–One-Form and the Principle of Independence will be operationalized in designing a complexity metric for grammatical gender. 3. Grammatical gender and dimensions of
gender complexity 3.1 Gender as a grammatical domain In this paper, I follow the most widely accepted definition of gender within the typological literature (Corbett 1991; Hockett 1958). Thus I define gender
as a type of nominal classification strategy that must be reflected beyond nouns, via agreement
patterns (Di Garbo 2014: 3). Under this definition I include both systems of the Bantu type (large number of genders)
and systems of the Romance
type (small number of genders). Following Croft (2001, 2003, 2013), however, I refer to agreement patterns
as indexation patterns. Accordingly, I define the entities
whose inflectional morphology
signals gender (e.g., pronouns, adjectives, verbs) as gender indexes (or gender
indexing targets) and the entities that trigger a given gender indexation pattern (i.e., nouns, pronouns, noun phrase referents) as indexation triggers. In Corbett’s (1991) terminology, indexes and indexation triggers
are referred to as agreement
targets and controllers, respectively.[7] In the remainder of this section, I provide
a short overview of the criteria
used for the synchronic classification of gender systems,
the debate over the origins of gender, and the function(s) of gender
in discourse. Synchronically, the gender systems of individual languages are usually
classified based on: (1) the number of gender distinctions (Corbett 1991, 2013a); (2) whether gender distinctions are sex-based
or non-sex-based based (Corbett 1991, 2013b); (3) the criteria according
to which nouns are assigned
to a given gender (Corbett 1991, 2013c). Diachronically, gender has been observed to be one of the most stable features of grammar. Gender systems are stable with respect to two of the three criteria
for stability proposed
by Nichols (1992): diachronic persistence and areal contingency. Gender is one of the most conservative features in the history of language families (stability as diachronic persistence). For instance, Armenian
is the only independent branch
of the Indo-European language family that has completely lost
grammatical gender. In addition,
gender systems exhibit a hotbed–outlier type of distribution (stability as areal contingency): some areas of the world, such as Africa or Australia,
are densely populated
by languages with gender (gender hotbeds), whereas in other
areas of the world (e.g., North America), the feature
is absent or attested only in isolated
cases (gender outliers). The debate over the origins
of gender is very controversial and, in many respects, still unresolved. On the one hand, it has been shown that gender
systems may originate
from classifier systems
and/or from demonstratives (Greenberg 1978; Corbett 1991). On the other hand, among the issues that are still open for debate is, for instance,
the question of whether indexation or classification comes first in the diachrony of gender within a given language or language
family (Nichols 1992). The main difficulty behind the reconstruction of the diachrony of gender in many language families is that, in view of their
overall stability, gender systems tend to presuppose long grammaticalization paths
and their origin often precedes
those stages that can be reconstructed via the historical-comparative method. Finally, from a functional point
of view gender has been defined
as a grammatical device for the management of reference in discourse, its functions being often related to reference tracking
(Heath 1975; Foley & Van Valin 1984) and/or discourse redundancy (Dahl 2004). The debate over the discourse functions
of gender is huge and cannot be extensively surveyed here (for an overview,
see Kilarski 2013: chapter 6, as well as Contini-Morava & Kilarski 2013). For the sake of this paper, suffice it to say that scholars
usually disagree on whether the complex redundancies that gender indexation introduces in discourse
facilitate communication (Dahl 2004) or exist beyond communicative necessity
(McWhorter 2001). Evidence from second language
acquisition is often brought in support of the latter argument:
contact varieties
that emerge as a result of intensive
post-threshold language contact and nonnative acquisition tend to systematically lack gender; similarly, adult learners usually struggle with grammatical gender when acquiring
a new language. 3.2
The dimensions of gender complexity Together with verbal inflection (Kusters 2003) and core argument
marking (Sinnema¨ki 2011), gender figures as one of the few areas of grammar
that have, so far, received
some attention in the literature on linguistic complexity. Perhaps this is because grammatical gender is one of the domains of grammar that most promptly leads itself to be associated with complexity, being both theoretically and empirically relevant for the study of such notions as inflectional morphology (Nichols 1992), maturity (Dahl 2004) and redundancy in information management (McWhorter 2001). Grammatical gender, in the form of gender indexation and overt gender distinctions on nouns, is one of the features
of the complexity metric
proposed by Nichols (2009). In this study, properties of gender systems are surveyed
together with properties of other nominal classification devices (numeral and possessive classifiers) under the label classification. Within the metric
proposed by Nichols,
presence of gender indexation and overt marking of gender on nouns feature
higher degrees
of complexity.[8] A more detailed qualitative study of the dimensions of gender complexity – viewed independently of other nominal
classification devices
– is Audring (2014). Audring argues that the complexity of gender systems
is tied to and can be investigated by taking
into considerations three main dimensions: complexity of values; complexity
of assignment rules; and complexity of formal marking. Dimension 1, complexity of values, is concerned with the number of genders
in a language:
the higher the number of genders, the more complex the gender system. Dimension 2, complexity of assignment rules,
is concerned with the type and scope of gender assignment rules. With respect to type of assignment rules, the literature on the typology
of gender systems
(Corbett 1991, 2013c) has shown that there exists two principles according
to which nouns are assigned to a gender in a given language: semantic and
formal. Under semantic assignment rules, gender assignment is predicted on the basis of the meaning of nouns. Under formal assignment
rules, gender assignment is predicted based on morphological rules (e.g., inflectional classes, derivational morphology) and/or phonological rules. In principle, the least complex gender system is one in which
only one type of assignment rule is attested, semantic or formal. In reality, typological studies of gender (Corbett
1991, 2013c) have shown that while solely semantic gender systems are relatively common
among the world’s languages
(e.g., among Dravidian
languages), gender systems
purely based on formal assignment rules are almost
never encountered. Even in those systems that are heavily
skewed towards formal
mechanisms of gender assignment, there is always at least a minimal portion of the nominal lexicon
(often nouns denoting humans and/or animate entities)
for which gender is
assigned based on clear-cut
semantic criteria.[9] As for the scope of assignment rules, this has to do with the degree of generality of a rule, that is the gender assignment of how many nouns a given rule is able to predict. The higher the number of nouns assigned to a certain
gender by a given assignment rule, the larger the scope of the assignment rule. In general,
a system with large assignment rules
requires a lower number
of rules, leading
to lower complexity. These rules usually
rests upon some basic
semantic notions such as sex or animacy
(Audring 2014: 11). Dimension 3, complexity of formal marking, is concerned with the pervasiveness of gender marking in discourse, that is, via indexation. The most straightforward implementation of this dimension of the complexity of gender is to count how many gender
indexes there are in a language based on how many
word classes inflect
for gender (e.g.,
pronouns, adjectives, verbs), and independently of how these inflections are realized in discourse. The higher the number of gender indexes, the greater the complexity of a gender system.
However, it is
also possible to explore this dimension of gender complexity by looking at discourse frequencies, that is by measuring how
often gender inflections appear in a given
chunk of discourse (the higher the frequency
of gender marking in discourse, the more complex the system). This aspect
of the complexity of gender (which will not be explored
further in this paper) can also be operationalized in the investigation of the functionality of gender indexation in language learning
and processing. In this sense,
a particularly promising hypothesis that is put forward in Audring’s (2014) work is that, pervasive gender indexation facilitates the learning and processing of gender values and assignment rules, given that users are exposed
to multiple occurrences of gender marking in a given chunk
of discourse. The gender system of English would rank low with respect to all three dimensions of complexity: it has only three genders,
a few semantic assignment
rules, and gender indexation is restricted to the pronominal domain. To sum up, Audring (2014) suggests that the absolute
complexity of gender systems can be explored
on the basis of three macro-dimensions: number of values,
assignment and indexation. This suggestion is followed
in the present paper. In section 4.2, I propose one way of implementing the three dimensions
into a complexity metric. 4. Methodology 4.1 Sampling procedure This study is based on a sample of 84 gendered
languages selected from the African macro-area and organized
in subsets of genealogically related
languages (the sample
languages are listed in alphabetical order
in appendix A).[10] The macro-area sampled in the study, Africa, is one of the world’s gender hotbeds (Nichols 1992, 2003): all major genealogical groupings
within the area display gender at least at some level of their internal taxonomies. The language classification followed in the paper is the one proposed by Glottolog (Nordhoff et al. 2013) as of September, 2015. The sample designed
for this study differs
from classical sampling
procedures in linguistic typology. Traditionally, these procedures aim to maximize
the representation of
linguistic diversity by contributing one datapoint (i.e., one language) per genealogical unit.[11] In recent years, statistically implemented sampling
methodologies that attempt
to investigate linguistic patterns
as distributed within language families have been proposed, for instance, by Maslova (2000) and Bickel (2013). The main assumption behind
these methodologies is that typological distributions concerning linguistic variables reflect
different historical scenarios that may
favor the presence/development/maintenance or, rather, the absence/decline/loss of the variables
in question. Accordingly, these
studies argue that it is possible
to explore “statistical biases
in diachronic developments on the basis of synchronic samples” (Bickel 2013: 415). The design of the present sample is built on similar assumptions. However the study does not focus on the elaboration of stochastic models of language change
based on the observation of synchronic distributions. The aim of the study is, in fact, mostly descriptive. What I am looking for is the degree of grammatical complexity that is associated with gender crosslinguistically and the extent to which this complexity is genealogically and areally uniform. The sample consists of seventeen different genealogical units (or lineages following the terminology by Nichols 1992), among which two isolates (Hadza and Sandawe). Some of these units represent different subgroups of the same superordinate taxonomic level (stock)[12]. In general, language
selection has been guided by the following
rule of thumb: the higher the diversity (in terms of number of languages/subgroups) of a superordinate genealogical unit,
the higher the number of languages/subgroups selected
for that unit. Consequently, the biggest and more diverse language families are represented by a number of subsamples
that tends to reflect this diversity. For instance,
all major subdivisions of the Afro-Asiatic stock (except
Egyptian) are represented in the sample.
The subsamples created for each stock should be understood as convenience samples since (1) the number of languages
per genealogical units is not established mathematically and (2) for the biggest stocks, not all subdivisions are included. The latter especially
applies to the largest
stock within the African macro-area, Atlantic-Congo. Some relevant genealogical units, such as Kru and, from the Volta-Congo sub-branch, Gur and Ubangi are, for
instance, not included in the sample mainly due to lack of accessible resources. This impacts data analysis
in that the data-set created for this study
cannot be used for statistical
analysis of the inferential type, that
is to make predictions about preferred typological patterns in the languages of Africa and beyond. Thus, as mentioned
above, the statistical analysis
that will be applied to the data presented in the study
is purely descriptive. Table
1 illustrates the number of genealogical units/languages per stock.
Table 1. Genealogical units in the sample 4.2 The features of the complexity metric The complexity metric that I designed for the purpose
of this study consists of six features. These can be further grouped into three main domains,
which are based on the three dimensions of gender complexity proposed
by Audring (2014) and discussed in section 3.2: complexity of values, complexity of rules and complexity of formal
marking. The features
of the complexity metric
are presented in table 2.
Table 2. Features
of the complexity metric and their description Features GV, AR and IND can be seen as direct implementations of Audring’s (2014) three dimensions of gender complexity. Complexity with respect to GV counts as a violation
of the Principle of Fewer Distinctions (the higher the number of gender distinctions, the more complex the system). Less straightforward is, on the other hand, the interpretation of AR and IND with respect to the three complexity principles outlined in 2.3. Here, I propose
to view complexity with respect to AR as a violation
of the Principle of Independence, and complexity with respect to IND as a violation
of the Principle of One-Meaning–One-Form (both on the syntagmatic and paradigmatic level) and the Principle
of Independence. On the one hand, systems of gender assignment that are dependent
only on semantics or only on form are less complex than systems of gender assignment that are dependent
both on semantics and form (violation of Principle of Independence). On the other hand, in a language
in which many word classes inflect for gender, and gender inflections are attested in several indexation domains (e.g., articles,
other adnominal modifiers, predicative expressions, pronouns): (a) information about the gender of a noun is likely to be repeated
redundantly in discourse (syntagmatic violation of the Principle of One-Meaning–One-Form); (b) the same word class can take several inflections depending
on the gender
of the noun that is indexed
in a given discourse
domain (paradigmatic violation of
the Principle of One-Meaning–One-Form
and Principle of Independence). Features M1, M2 and CUM are based on an aspect of the typology of gender that falls outside the scope of Audring’s
work: how grammatical gender interacts with other nominal
domains. Two domains are specifically targeted by my metric: number and evaluative morphology (i.e., the morphological encoding of diminutives and augmentatives).[15] M1 and M2 are concerned with interactions at the level of gender assignment whereas CUM has to do with interactions pertaining to the morphosyntactic encoding of gender
distinctions on the indexing
targets. I suggest that M1 and M2 can be interpreted as a violation of the Principle of Independence, and CUM as a violation
of the Principle of One-Meaning–One-Form. Let us discuss
these two types of interaction more in detail. Di Garbo (2014) shows that an important criterion for the classification of gender systems in the African
macro-area is to distinguish between
rigid and manipulable
gender assignment (for as similar suggestion, see also the study by Heine 1982). In languages with manipulable gender assignment, the gender of a noun can be changed depending
on the construal of the noun phrase referent, that is based on pragmatic/discourse constraints. In these languages, there usually are default assignment rules, i.e., rules by which nouns have lexically specified
gender values, and add-on assignment rules that allow speakers to modify the default
meaning of the noun by changing
its gender, thus changing
the construal of the noun phrase referent. In Di Garbo’s sample,
manipulable gender assignment is attested in connection with two main uses: (1) to encode variation in the countability properties
of nouns (e.g., from uncountable to countable and vice versa), (2) to encode variation
in size (diminutive vs. augmentative). In my metric,
I refer to the first use of manipulable gender assignment as M1[16] and to the second as M2. M1 is illustrated in example (1) and M2 in example (2). The examples
are taken from two Berber languages, Nefusi and Tachawit.[17]
In example (1) (taken from Nefusi),
when the inherently masculine uncountable noun ettefˆah̩ ‘apples’ is shifted
to the feminine gender (as in (1b)), it becomes countable and can be thus regularly
pluralized (as in (1c)) (in Berber, feminine
gender marking on nouns is circumfixal both in the singular
and in the plural). This is an instance of M1. In Tachawit
(example (2)), inherently masculine nouns can be shifted to the feminine gender when a diminutive interpretation is intended for the noun phrase referent
(as in (2a) and (2b)). Similarly, an inherently feminine noun can be assigned
to the masculine gender when an augmentative interpretation is intended for the noun phrase referent (as in (2c) and (2d)). This is an instance
of M2.[18] In general M1 and M2 are well attested in the languages of Africa, both in
languages with large, non-sex-based gender
systems and in languages with smaller sex-based
systems. Within my sample, M2 is however more frequent
and widely distributed than M1 (for an overview, see Di Garbo 2014: chapters 5 and 6). The possibility of manipulating gender assignment can be seen as piling on top of the default
gender assignment
rules that are used in a language.
In languages with manipulable gender assignment, gender
markers have default and add-on meanings.
These add-on meanings are dependent on semantic and pragmatic associations between
gender and other grammatical domains, notably countability and size/value. Thus, based on the Principle
of Independence introduced above, their presence represents an increase in the absolute
complexity of gender.
Gender assignment is not only given in the lexicon for each and every noun, but it is also subject to change depending on semantic
and pragmatic associations with other functional domains. Feature CUM (cumulative encoding of gender and number on the indexing targets) evaluates the impact that type of exponence
of gender and number has on the complexity of gender. I interpret cumulative encoding of gender and number as a violation
of the Principle of One-Meaning–One-Form (one morpheme expresses several grammatical meanings). One aspect of the morphosyntactic encoding of gender and number which,
at least in the languages
of my sample, appears to be strictly
related to CUM is the tendency
for gender distinctions to be reduced (syncretism) or lost (neutralization)
in the context of non-singular number values. In my sample, syncretism and/or neutralization of gender in the context of nonsingular number
occurs in 66 out of 84 languages; in nearly all these cases the languages in which syncretism is
attested are also languages in which gender and number are encoded cumulatively (see also results
in Di Garbo 2014: chapter 5).[19] In principle,
gender syncretism and neutralization could be viewed as violations of the Principle of Independence inasmuch
as, when they occur, the expression
of gender within an inflectional paradigm depends on the number value of a noun. In addition,
syncretism and neutralization could be also seen as violations of the Principle
of One-Meaning–One-Form, given that two (or more) gender values are conflated into one in the context
of non-singular number
values. However, as Audring (forthcoming) points out, “[s]yncretism is a
multifaceted phenomenon, and whether or not it should be considered a case of simplification or complexification depends on the perspective”. In this paper, I treat syncretism in a somewhat agnostic
way and exclude
it from my complexity metric. More research,
I believe, is needed on the relationship between
syncretism/neutralization, exponence, and paradigm size before
we can assess the effects of syncretism/neutralization on the complexity of gender and related features (e.g., number and case) more
confidently. 4.3 Method for computing Gender Complexity Scores Having defined the features for measuring the absolute complexity of grammatical gender (see table 2), the next step is to establish the values associated with each feature and to convert them into numbers. Towards this aim, I follow Parkvall (2008) who designed a method for computing the grammatical complexity of creoles and non-creole languages on the basis of a set of features taken from the WALS database (Dryer & Haspelmath 2013). Within Parkvall’s method, the values of each feature are assigned a number between 0 and 1. Features with three values are converted into the numerical format 0, 1/2, 1. Similarly, features with five values are converted by Parkvall into the format 0, 1/4, 1/2, 3/4, 1. For all the features taken into account in Parkvall’s paper, 0 stands for minimally complex and 1 for maximally complex. The total complexity score for each language is divided by the number of features included for that language. This is done in order to allow languages for which less information is available on a given feature to get average scores comparable to those of the best documented languages. The same procedure is followed in this paper (naturally, features with four values are converted into the numerical format 0, 1/3, 2/3, 1). The feature values and their numerical interpretation are illustrated in table 3.
Table 3: Gender complexity metric The composition of the metric is such that the least complex possible
gender system is the one that scores zero with respect
to all the features of the metric and exhibit
the following properties: two gender values,
semantic gender assignment, one indexing
target, no cumulation with number, no manipulation of gender assignment triggered
by number/countability and no manipulation of gender assignment triggered by size. On the other hand, the most complex
possible gender system is the one that scores
1 with respect to all the parameters considered in the metric and exhibits
the following properties: five or more genders, semantic and formal assignment, four or more indexing
targets, cumulation with number, and manipulation of gender assignment triggered by both number/countability and size. In addition, the composition of the metric is such that, with the exception of languages
with the highest
score (= 1), languages may display the same index value but arrive to it on different paths. In other
words, identical gender complexity scores (henceforth GCSs) do not stand for same type of gender
system. Before presenting the results of my calculations, it is worth mentioning that, in case of missing features, the index values
resulting from the calculations should be taken with caution.
In fact, even though average scores
(rather than total scores) are used as index values, the index values of languages
with missing features cannot be regarded
as entirely comparable to the index values of languages for which all features are equally
represented. The mutual comparability between
the different
domains of gender
complexity covered by my metric
is discussed in section 6.3. 5. Results Table 4 illustrates the GCSs of the languages of the sample,
which have been calculated based on the method presented
in section 4. The table is divided in two macrocolumns and the GCSs of the individual languages are arranged
from highest to lowest. The leftmost columns of each macro-column provide
the rank: languages with the same average complexity score share the same rank.
Next to the rank come the language
names and their
ISO code; the GCS assigned
to each language
is given in the rightmost columns of the two macro-columns. In appendix C, the GCSs are visualized on the basis of genealogical units. The complexity scores
for each of the feature
values in the metric,
as well the GCSs, are given in appendix
B.
Table
4: GCSs of the languages of the sample Table 4 shows that the highest GCS is 1 and the lowest 0.08. None of the languages of my sample thus gets the lowest possible
score, 0 (see section 4.3). The results given in table 4 are also displayed
in the graph in figure 1. The X-axis of the histogram
displays the range of attested
GCSs, whereas the Y-axis shows the distribution of the number of languages
per GCS score. The box plot below the histogram provides
the distribution of the GCSs per quartiles, with the boldface line in the middle representing the median. The figure shows that half of the languages of my sample have a GCS that ranges roughly from 0.5 to
0.8. In my data sample, high GCSs are substantially more frequent than low GCSs. Figure 1: Distribution of the GCSs The geographical distribution of the GCSs is represented in the map provided
in figure 2. Figure 2: Geographical distribution of the GCSs The results presented in table 4, figure 1 and 2, as well as in appendix C, are discussed
in section 6 based on three main foci:
Before moving on to the discussion, I illustrate the procedure followed to calculate the GCSs of two of the sampled languages.
For the sake of clarity, I discuss one language for which all features are documented, Turkana (Eastern
Nilotic, rank 3 in table 4), and one for which two features are missing, Timne (Mel, rank 1 in table 4). My classification of the gender system
of Turkana is based
on Dimmendaal (1983). Turkana has three gender values: Masculine,
Feminine and Neuter. It thus gets 1/3 with respect to the feature GV. Gender assignment is both semantic and formal, and, as such, the value of AR is 1. According to Dimmendaal, gender indexation appears in three domains: articles
(definite articles), adnominal
modifiers, and pronouns
(not the Personal
Pronouns). Thus the language gets 2/3 with respect to the feature
IND. In Turkana, gender distinctions are encoded cumulatively with number (CUM = 1). Finally,
in Turkana gender shifts can be used to encode variation
both in the countability properties
of nouns (M1 = 1) and in the size of the
noun phrase referent (M2 =
1). In Turkana, when an uncountable masculine or feminine
noun is shifted to the Neuter Gender,[22] the resulting
meaning is singulative. On the other hand, when countable masculine
or feminine nouns are shifted to the Neuter Gender, the resulting
meaning is diminutive. To summarize, for Turkana,
the values assigned to each feature
of the metric are: GV = 1/3; AR = 1; IND = 2/3; CUM = 1; M1 = 1; M2 = 1 Applying the formula illustrated in section 4 [(⅓+1+⅓+⅔+1+1+1)÷6]
the GCS of 0.83 is obtained. I classify the gender
system of Timne based
on the description provided
by Wilson (1961). Timne has more than five genders and thus gets 1 with respect to the feature GV. Gender assignment is both semantic
and formal. Therefore,
Timne gets 1 with respect to the feature AR. According to Wilson’s
description, Timne shows gender indexation on adnominal modifiers, pronouns, predicative expressions. In addition, in Timne, the Indefinite Stabilizer, which
is used with indefinite nouns in order to encode non-verbal predication (Wilson 1961: 11), also inflects for gender (this is labeled as “other” in my coding).
The language thus gets 1 with respect to IND. Gender
and number are encoded cumulatively on the indexing targets (CUM=1).
The source does not provide any kind of information about gender shifts, which are, however, rather common phenomena
in languages with similar gender systems. The features M1 and M2 cannot be documented
for Timne. To summarize, for Timne, the values assigned
to each of the metric features are: GV = 1; AR = 1; IND = 1; CUM = 1; M1 = –; M2 = – Since two features
are missing, the sum of the feature
values is in this case divided
by 4 [(1+1+1+1) ÷ 4]. The GCS of Timne is thus 1. 6. Discussion 6.1 Genealogical and areal biases in the distribution of
GCSs In appendix C, the GCSs presented in table 4 are visualized on the basis of genealogical units. The tables in appendix
C show that, in general, closely related languages tend to have the same or very similar GCSs. For instance, all the Berber languages in the sample have a gender complexity score of 0.69. This tendency towards intragenealogical homogeneity in the complexity of gender systems
further supports the idea that grammatical gender is a
chiefly stable feature in the history of language
families (see section 3.1). Nevertheless, outliers (i.e., languages that exhibit a GCS that is
exceedingly higher or lower than what found
among closely related languages) are attested
in the following genealogical units: Bantu, Chadic, Cushitic, Khoe-Kwadi, Eastern Nilotic, Semitic.
I suggest that, at least in some of such cases,
the distribution of the outliers can be accounted for by taking
into consideration aspects of the social history of the
speech communities in question (e.g., geography, number of speakers, number of contact languages, type of language
contact, bilingualism, multilingualism). This is however
only a preliminary suggestion, which would need to be investigated further in what goes beyond the scope of the present study. Out of 84 languages, 18 scored 1, with all these being either
Bantu, North- Central Atlantic
or Mel. Typically, the gender systems of the Bantu and Atlantic type (i.e.,
North-Central Atlantic and Mel) exhibit features
of high complexity: high number
of gender distinctions, pervasive gender
indexation, manipulability of gender assignment, which is used to express variation in the countability properties of nouns and/or
in the size of the noun phrase
referents. Those Atlantic
and Bantu languages which rank lower than 1 in table 4 have gender systems in which one or more of the above-mentioned features has/have been either weakened
or lost. For instance, in 8 of the 23 Bantu languages
in the sample – Bafia,
Eton, Northern Sotho, Shona,
Swati, Tswana, Venda, Zulu – diminutive and augmentative suffixes have grammaticalized
from nouns. Of these eight languages, only Venda and, to a lesser extent, Shona combine the use of the diminutive and augmentative suffixes with the uses
of the dedicated diminutive and augmentative genders that are
characteristic of many Atlantic-Congo languages.[23] In the remaining
six languages, the evaluative genders
have been lost. As a result,
the complexity of the gender systems of these languages is lower than what found in other closely
related languages. Two outliers with respect to the Bantu and Atlantic
type of gender
system are the Bantu languages Kinshasa
Lingala (GCS = 0.22)
and Bila (GCS = 0.16).
My coding for Kinshasa
Lingala, the variety
of Lingala spoken
in the area of the capital city of the Democratic
Republic of Congo,
is based on Bokamba (1977) and Meeuwis (2013). Kinshasa Lingala preserves the system of noun class marking
which is typical of Bantu languages only on nouns. Meeuwis (2013) rightly refers to this set of singular/plural pairs of nominal
prefixes as inflectional classes: diachronically, they are a relic of the former Bantu-like gender system, but, synchronically, they merely function
as markers of nominal number. The Third Person Pronouns and
the Subject Prefixes index the animacy of the noun phrase referent.
Based on this account, I classify
Kinshasa Lingala
as a language with two genders
(Animate and Inanimate), semantic
gender assignment and two domains of gender indexation (pronominal and predicative). Compared to Makanza Lingala, the northwestern variety of Lingala whose origins go back to the language
standardization policies operated by the Scheutist missionaries between
1901 and 1902,
and which exhibits
a more conservative gender
system, the gender system of Kinshasa
Lingala is massively reduced.
According to Meeuwis (2013: 26), Kinshasa Lingala is the oldest variety and the direct descendant of the Bangala pidgin, which was originally spoken in the Bangala state post (on the northwestern banks of the Congo River) and later on
spread northeastward.[24] This variety resisted to the grammatical reforms introduced by the Scheutists, and
soon gained both native and second language speakers.
The pidginization process from which Lingala originated, as well as the highly multilingual ecology in which the Kinshasa
variety developed and expanded, can reasonably explain the patterns of simplification and reduction in the domain
of grammatical gender
that differentiate this variety from other Bantu languages, on the one hand, and from the standardized variety introduced by the missionaries in the northwestern areas of the Democratic Republic of Congo (Makanza Lingala), on the other
(on this account,
see also Bokamba 1977, 2009). Similarly to Kinshasa Lingala,
Bila has only two genders (the Animate and the Inanimate Gender), semantic
assignment rules and poor gender indexation. Differently from Kinshasa Lingala, however, gender
indexation in Bila is exclusively internal to the noun phrase
and limited to the domain
of adnominal modifiers (Kutsch
Lojenga 2003: 462). Bila is spoken in the northeastern part of the Democratic Republic
of Congo, which is also the northernmost corner of the Bantu-speaking area. The northern
part of the Bantu-speaking area is often described as a true borderland between linguistically very diverse communities that have extensive
contact with each other. In this area, Bantu speakers
are surrounded by speakers of Nilo-Saharan and Ubangi languages (Kutsch
Lojenga 2003: 451-452). Due to intense
mutual contact, both the Bantu and non-Bantu languages spoken in this area are characterized by massive lexical
borrowing as well as by grammatical innovations that are not shared with the respective cognate
languages outside the area. The reduced
gender system of Bila and other
neighboring Bantu languages is one of such area-specific features. The Semitic languages provide another
interesting illustration of a set of genealogically related languages with non-homogeneous GCSs. The highest
ranking GCSs within the Semitic
sample go to Maltese ( 0.78) and Amharic (0.67). Moroccan Arabic,
Standard Arabic and Tigre have the same complexity score,
0.61. The lowest ranking gender system is found in Hebrew (0.45), whereas Lisha´n Dida´n scored 0.53. Interestingly, the highest GCS, 0.78, is scored by Maltese, the Semitic language that stands out for its peculiar history
of long-term contact
and bilingualism with English, on the
one hand, and Romance languages (Italian and Sicilian), on the other. A similarly
high GCS goes to Moroccan
Arabic, a dialect of Arabic whose history is also characterized by long-term intense contact with Berber languages,
French and Spanish (for a case study of complexity of verbal inflection in Moroccan Arabic and other varieties of Arabic, see Kusters 2003). Finally, the history of Modern (Israeli) Hebrew is also intertwined with intricate sociolinguistic dynamics involving
processes of creolization, language shift and massive borrowing (see, among others,
Doron 2015; Zuckermann 2009). Two additional examples of outliers are Dahalo, with respect to the other
Cushitic languages, and Kwadi, with respect to the Khoe-Kwadi group. Dahalo has a GCS of 0.28, and its gender system has been described
by Tosco (1991: 20) as dying out as a result of contact with neighboring Bantu languages. Too little is known about Kwadi, a now extinct
language of Angola.
Gu¨ldemann (2004) describes its gender system as sex-based and pronominal, but not much information is given about mechanisms of gender assignment nor about the use of gender shifts to encode
diminutive and augmentative meanings
(which is well documented in all the other Khoe-Kwadi languages of the sample). Finally, the two lowest ranking languages in the complexity rank given in table 4 are the Chadic languages Mwaghavul (GCS = 0.08) and Pero (GCS = 0.12), both of which are spoken in Nigeria. The two languages also qualify as outliers with respect to the other Chadic languages in the sample. Mwaghavul scores 0 with respect to all the features of the complexity metric except for CUM, for which the score is 0.5. There are two genders in Mwaghavul (Masculine and Feminine), gender assignment is semantic and gender indexation is only pronominal. Finally, there seems to be no possibility of manipulating gender assignment in the language. With respect to the cumulation parameter, Mwaghavul shows at least some patterns of interaction with number on the indexing targets. The Third Person Human Anaphoric | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||