10.6092/issn.2785-0943/17482
We examine a database of 3089 languages coded for 351 morphosyntactic features, including almost all of the morphosyntactic features found in The World Atlas of Language Structures (Dryer &amp; Haspelmath 2013). We apply Factor Analysis of Mixed Data, and determine that the main dimensions of global morphological variation involve (1) word order in clauses and adpositional phrases, (2) head- versus dependent-marking, and (3) a set of features that show an east-west distribution. We find roughly the same features clustering in similar dimensions when we examine individual macro-areas, thus confirming the universal relevance of these groupings of features, as encapsulated in well-known implicational universals. This study confirms established insights in linguistic typology, extending earlier research to a much larger set of languages, and uncovers a number of areal patterns in the data.
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The Dimensions of Morphosyntactic Variation: Whorf, Greenberg and Nichols were right
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<p>Whorf, Benjamin Lee. 1941. The Relation of Habitual Thought and Behavior to Language. In Leslie Spier, A. Irving Hallowell &amp; Stanley S. Newman (eds.), <em>Language, Culture, and Personality: Essays in Memory of Edward Sapir</em>, 75&ndash;93. Menasha, Wisconsin: Sapir Memorial Publication Fund. Reprinted in John B. Carroll (ed.) 1956. Langu<em>age, Thought and Reality. Selected Writings of Benjamins Lee Whorf</em>. Cambridge, Mass: The MIT Press.</p>
The Dimensions of Morphosyntactic Variation: Whorf, Greenberg and Nichols were right
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3
               Linguistic Typology at the Crossroads 3-2 (2023): 132-190                     ISSN 2785-0943



          The Dimensions of Morphosyntactic Variation:
                  Whorf, Greenberg and Nichols were right

                                   SIVA KALYAN1 & MARK DONOHUE2
           1
            THE UNIVERSITY OF QUEENSLAND & THE AUSTRALIAN NATIONAL UNIVERSITY,
                     2
                      THE LIVING TONGUES INSTITUTE FOR ENDANGERED LANGUAGES




                          Submitted: 27/06/2023               Revised version: 23/10/2023
                             Accepted: 27/11/2023                  Published: 27/12/2023



                         Articles are published under a Creative Commons Attribution 4.0 International License (The authors
                         remain the copyright holders and grant third parties the right to use, reproduce, and share the article).




                                                         Abstract
We examine a database of 3089 languages coded for 351 morphosyntactic features, including
almost all of the morphosyntactic features found in The World Atlas of Language Structures
(Dryer & Haspelmath 2013). We apply Factor Analysis of Mixed Data, and determine that the
main dimensions of global morphological variation involve (1) word order in clauses and
adpositional phrases, (2) head- versus dependent-marking, and (3) a set of features that show
an east-west distribution. We find roughly the same features clustering in similar dimensions
when we examine individual macro-areas, thus confirming the universal relevance of these
groupings of features, as encapsulated in well-known implicational universals. This study
confirms established insights in linguistic typology, extending earlier research to a much
larger set of languages, and uncovers a number of areal patterns in the data.


Keywords: typology; word order; morphosyntax; head/dependent-marking, computational
linguistics; areality.



1. Introduction


The goal of much early work in linguistic typology was to categorise languages into
distinct overall “types”, under the assumption that once the type of a language was
known, a large number of its features could then be predicted – in effect, a holistic


https://doi.org/10.6092/issn.2785-0943/17482                                                                           132
Linguistic Typology at the Crossroads 3-2 (2023): 132-190


approach to typology (Croft 2003: 31, Humboldt 1836, von der Gabelentz 1901).
While the prominence of such taxonomic work has receded in favour of detailed
studies of individual features (or clusters of related features), the time is ripe to
resuscitate such work in light of the increased amount of linguistic data that has
become available. In this paper, we use Factor Analysis of Mixed Data (FAMD; Pagès
2004) to determine the main dimensions of global typological variation in
morphosyntax – that is, the features that are most helpful for dividing the world’s
languages into different morphosyntactic types. We use a large database of
morphosyntactic features, built and substantially expanded from the WALS dataset
(Dryer & Haspelmath 2013; see Appendix 2), with both features and languages chosen
independently of the present study. Upon examining the principal dimensions
emerging from this analysis, we find that in each case, they bring together a group of
features that has previously been proposed as a basis for the global typological
classification of languages: in particular, we find groups of features relating to (mostly
clausal) word order (proposed as a basis for classification by Greenberg 1963, refined
by Dryer 1992, 2013, and other publications; Dimensions 1 and 4; sections 3.1.1 and
3.1.4), head/dependent marking (Nichols 1986; Dimensions 1 and 2; sections 3.1.1
and 3.1.2), and a set of features that define a global east-west split, one end of which
is mainly present in the Old World, and the other end of which is dominant in the
“Circum-Pacific” region (Bickel & Nichols 2006, Bugaeva et al. 2021; section 3.1.3).
     The remainder of this paper is structured as follows. In section 2, we introduce our
dataset (World_morphosyntax), the metadata used as controls, and the technique of
FAMD. In section 3, we present our results, for the global set of languages as well as
for each macro-area individually; we find that the groupings of features that emerge
in the global analysis recur in individual macro-areas. In section 4 we examine some
of the negative results, discussing the kinds of features that have the smallest
contribution to the global analysis. Finally, in section 5 we summarise our findings,
and suggest directions for future research. A number of appendices illustrate the
distribution of the individual features that emerge as relevant to defining the four
dimensions described in section 3.1




1
    Appendices are available as supplementary material at:
https://typologyatcrossroads.unibo.it/article/view/17482/17369


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Kalyan & Donohue                                                 Dimensions of Morphosyntactic Variation


2. Data and methodology


The World_morphosyntax dataset consists of 3089 language varieties (rows—see
Appendix 10), representing 2,693 distinct iso 639-3 codes,2 coded for 351
morphosyntactic features (columns). It is curated by Mark Donohue (see Appendix 1),
and has been developed since 2010. The original database was based on the most
robustly coded languages and features from the World Atlas of Language
Structures (Dryer & Haspelmath 2013). The dataset includes most of the 155
morphosyntactic features in WALS, with unordered multivalued features recoded as
sets of binary features. (See Appendix 2 for a full listing and description of the features
in the World_morphosyntax dataset.) For instance, WALS feature 57A (‘Position of
Pronominal Possessive Affixes’) is coded as a single feature in WALS, consisting of the
features listed in (1).


(1)      WALS feature 57A ‘Position of Pronominal Possessive Affixes’


a.       Possessive prefixes
b.       Possessive suffixes
c.       Prefixes and suffixes
d.       No possessive affixes


We have recoded this single, categorial, features into three binary features, and added
an additional feature, as listed in (2). This recoding captures the variation in WALS
feature 57A, in M72 and M73; the ‘Prefixes and suffixes’ values of WALS 57A is coded
with positive values for both of M72 and M73, thus showing commonality with both
prefixal languages and suffixal languages, which is not automatically extracted from
the WALS coding. Positive values for M72 and M73 are unified by M71, which
captures the commonality between prefixal and suffixal marking in that both do
represent the coding of features of the possessor on the possessum. M70 adds in a
typologically-attested variable that is not coded in WALS.




2
    The most doubled iso codes are cmn (Mandarin varieties), zlm (Malay varieties), adi (Tani languages),
each of which has ten or more entries, at least some of which represent different languages by any
normal criteria.


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Linguistic Typology at the Crossroads 3-2 (2023): 132-190


(2)   Features M70 – M73


a.    M70       Possession: associative tone           +/–
b.    M71       Possessive affixes: any                +/–
c.    M72       Possessive affixes: prefixes           +/–
d.    M73       Possessive affixes: suffixes           +/–


In addition to recoding some of the WALS features, additional features were added.
WALS feature 102A codes for the appearance of agreement for A or P arguments. We
have added coding for an S argument, as well as a third argument (M238), to account
for languages that allow a recipient or dative argument to appear indexed on the verb.
Very rarely a fourth or fifth agreement position can be found, and these are also
coded, as M243 and M244. Additionally, just as WALS codes the position of agreement
affixes marking possession on nouns, as prefixal or suffixal, we add in coding for the
position of agreement affixes on verbs, as shown in (3).


(3)   Coding the position of verbal agreement


a.    M232 verb agreement_S prefix                  +/–
b.    M233 verb agreement_S suffix                  +/–
c.    M234 verb agreement_A prefix                  +/–
d.    M235 verb agreement_A suffix                  +/–
e.    M236 verb agreement_P prefix                  +/–
f.    M237 verb agreement_P suffix                  +/–
g.    M239 verb agreement_R/D prefix                +/–
h.    M240 verb agreement_R/D suffix                +/–
i.    M245 verb agreement_tone A                    +/–
j.    M246 verb agreement_tone S                    +/–
k.    M247 verb agreement_tone P                    +/–


Other WALS features that were recoded in order to enhance their matching with a
related feature in the database are the features devoted to morphological causatives.
These were recoded in line with the features focusing on applicatives (which were
also expanded). In WALS applicatives are coded for the kinds of bases that allow
applicative extensions (intransitive or transitive bases), and the semantic role of the



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Kalyan & Donohue                                      Dimensions of Morphosyntactic Variation


applied object (Benefactive, Instrumental, or Locative) (Polinsky 2013), and (non-
periphrastic) causatives are coded according to whether they are morphological or
compounds (Song 2013). In the World_morphosyntax database the range of semantic
roles   for   applicatives   was   expanded   (Benefactive,    Instrumental,      Locative,
Associative/Comitative, Theme, Reason, and Malefactive), and the types of bases
allowed were extended to query ditransitive bases, and to distinguish whether
agentive or patientive intransitive bases (or both) permit applicatives. Additionally,
the possibility of more than one applicative appearing on a single base was coded
with two features, as well as the possibility that the ‘applicative’ construction
promotes directly to subject (a ‘superapplicative’, as attested in many languages of
Taiwan and the Philippines). Matching the detail on applicative constructions present
in WALS and expanded on in World_morphosyntax, we coded morphological
causatives according to whether they are attested in patientive or agentive
intransitive bases, or even on ditransitive bases, as well as whether double (or second)
applicatives are attested with different bases, what the coding strategy is for the
causee of a causative construction with three arguments, and whether there is
syncretism between the morpheme used for causatives and applicatives.
  Other added features logically extend the scope of WALS features (for instance,
explicitly coding more semantic roles that can be introduced with applicative
constructions, the existence of suppletive negative verbal stems, or morphological
processes other than prefixation and suffixation - namely, infixation, and metathesis).
Wholly new features centre around the possibilities for nominal incorporation into
verbs. Further details on the features in the database can be found in Appendix 2.
  On average, the coding of languages reported here from the World_morphosyntax
dataset is 86% complete; this compares favourably with WALS (18% of 155 features
for 2662 languages), as well as more recent datasets such as Grambank (Skirgård et
al. 2023; 76% of 195 features for 2430 languages); see Appendix 1. For this study, we
excluded known pidgins and creoles, reconstructed proto-languages, and ancient or
historical languages. Pidgins and creoles frequently represent lineages that are not
original to the area in which they are currently found, and in most cases represent
disruptions to the local typological landscape. Ancient or historical languages (i.e.
those that are attested only before the era of European colonisation) are by definition
not part of any modern linguistic ecology, and so should not be included in an analysis
of modern languages. Excluding these, we were left with 3089 languages/varieties,




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Linguistic Typology at the Crossroads 3-2 (2023): 132-190


the locations of which are shown in Map 1.3 (See Appendix 1 for a full listing of the
languages, with their genealogical and areal memberships.)
     To analyse the World_morphosyntax dataset, we used Factor Analysis of Mixed Data
(FAMD; Pagès 2004), a dimensionality reduction technique that combines Multiple
Correspondence Analysis (MCA) and Principal Components Analysis (PCA), as
implemented in the FactoMineR package for R (Lê et al. 2008; see the Supplementary
Materials for our annotated source code). Since MCA is suited for data consisting
exclusively of categorical variables, and PCA is suited for data consisting exclusively of
continuous variables, we felt that FAMD is the appropriate choice for the
World_morphosyntax dataset, which contains 27 ordinal variables (which we treated as
continuous) and 324 binary variables. We started by imputing4 the missing values in the
dataset using the regularised iterative FAMD algorithm, as implemented in the
“imputeFAMD” function in the missMDA package for R (Josse & Husson 2016), using 4
components (though the number of components made little difference to the results).




              Map 1: Languages and language varieties included in the analysis (n = 3089).



3
    Legend: The map (as well as subsequent maps) shows the world from 60º S to 90º N, and from 30º
west extending 360º to the east.
4
    Imputation is a family of techniques for replacing missing values in a dataset with estimates of the
most likely values of those data points. It is necessary to perform imputation when applying techniques
such as FAMD, since such techniques involve computing a covariance matrix, which requires complete
data. The iterative FAMD algorithm for imputation (which we use here) works by first replacing
missing values in each column with the column mean; then performing FAMD; then reconstructing the
missing values based on the FAMD result; then performing FAMD again; and so on until the imputed
values stabilise.


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Kalyan & Donohue                                           Dimensions of Morphosyntactic Variation


We then applied FAMD to the imputed data, assigning weights to languages in a way
that equalises the total weights of different macro-areas, as well as of the different
AUTOTYP areas within each macro-area; this was done to increase the likelihood that
the dimensions that we find would capture groupings of features that are valid across
different macro-areas, and across different areas within each macro-area. Macro-areas
were defined according to Hammarström & Donohue (2014), itself a refinement of
the macro-areas established by Dryer (1989, 1992), with the exception that languages
belonging to the AUTOTYP “North Africa” area were re-assigned from Africa to
Eurasia, on the grounds that whereas the Sahara Desert has been a barrier to contact
since the end of the African Humid Period (e.g., de Menocal et al. 2000), cross-
Mediterranean societies have flourished since antiquity. The two different macro-area
divisions are compared in Maps 2 and 3. Most of the changes involve the
abandonment of the apparent principle of unifying families into single macro-areas,
and the split of Australia and (some of) New Guinea into separate macro-areas.




                      Map 2: Six macro-areas, following Dryer (1989, 1992).

Legend: 1: Africa; 2: Eurasia; 3: Southeast Asia and Oceania; 4: Australia-New Guinea; 5: North
America; 6: South America.




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Linguistic Typology at the Crossroads 3-2 (2023): 132-190




         Map 3: Six macro-areas, following Hammarström and Donohue (2014), amended here.

Legend: 1: Africa; 2: Eurasia; 3: Pacific; 4: Australia; 5: North America; 6: South America.


The    AUTOTYP    areas were extrapolated from those described in Bickel et al. (2023),
following Bickel (2002) and Nichols et al. (2013) (also https://www.autotyp.uzh.ch),
with a few major differences: (1) ‘Southeast Asia’ has been split into Mainland
Southeast Asia (consisting of the Southeast Asian languages of mainland Eurasia and
Hainan) and Island Southeast Asia (consisting of the remaining Southeast Asian
languages, as well as languages from ‘Oceania’ west of New Guinea and up to Taiwan),
and Madagascar has been moved to Africa, allowing the smaller areas to be embedded
unproblematically into macro-areas (as shown in Table 1); (2) The Andaman islands
are grouped with “Indic”, based on historical connections; (3) The languages of the
Aleutian Islands are included in ‘Alaska-Oregon’, rather than ‘North Coast Asia’, based
on geography and cultural connections. The different areas are shown in Map 4,
contrasting the original Autotyp areas with the modified set used here.5 Details of the
assignment of individual languages to areas can be found in Appendix 1.




5
    Legend for Map 4: 1: S Africa; 2: African Savannah; 3: Greater Abyssinia; 4: N Africa; 5: Greater
Mesopotamia; 6: Europe; 7: Indic; 8: Inner Asia; 9: Southeast Asia (mainland); 10: Oceania; 11: N Coast
New Guinea; 12: Interior New Guinea; 13: S New Guinea; 14: N Australia; 15: S Australia; 16: N Coast
Asia; 17: Alaska-Oregon; 18: E North America; 19: Basin and Plains; 20: California; 21: Mesoamerica;
22: Andean; 23: NE South America; 24: SE South America; 25: Island Southeast Asia.


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Kalyan & Donohue                                             Dimensions of Morphosyntactic Variation




            Map 4: The 25 modified AUTOTYP areas compared to the original 24 areas.


We are aware of alternative ways of controlling for area and genealogy (e.g.
Guzmán-Naranjo & Becker 2021 on phylogenetic regression and Gaussian processes;
Macklin-Cordes & Round 2022 on phylogenetic weighting). However, we opted to
stay with areally-weighted FAMD, for the sake of simplicity, and because the
patterns we find are strong enough to be visible and consistent regardless of what
controls we use (see Appendix 4).

        Macro-area                Modified AUTOTYP area (25)              n (languages)
                (6)
       Africa             Africa, African Savannah, Greater Abyssinia                  535
       Eurasia            N Africa, Greater Mesopotamia, Europe, Inner                1024
                          Asia, Southeast Asia (mainland), N Coast Asia
       Pacific            Island Southeast Asia, N Coast New Guinea,                   760
                          Interior New Guinea, S New Guinea, Oceania
       Australia          N Australia, S Australia                                     205
       North America      Alaska-Oregon, E North America, Basin and                    283
                          Plains, California, Mesoamerica
       South America      Andean, NE South America, SE South America                   282


                      Table 1: Modified AUTOTYP areas arranged by Macro-area.


Another advantage of using areal divisions as a control is that the difference in size
between the smallest group and the largest group is less than the difference between
the size of the smallest language family or genus (namely 1) and the largest. This
means that the area-based controls do not give undue weight to isolates and singleton



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Linguistic Typology at the Crossroads 3-2 (2023): 132-190


genera. An additional advantage of using areas, rather than genealogies, is that we
avoid having to make decisions about controversial language families like Nilo-
Saharan (Dimmendaal 2011), Trans-New Guinea (Pawley & Hammarström 2018),
Transeurasian/Altaic (Clauson 1956, Schönig 2003), Austric (Schmidt 1906, Reid
2005), Hokan and Penutian (Campbell 1997, DeLancey & Golla 1997, Poser 1995),
or Dene-Yeniseian (Kari & Potter 2010), or subgroups within families (e.g., Indo-
Iranian and the position of Nuristani languages within Indo-European, the existence
of Italo-Celtic in the same family, or the internal hierarchy of Tibeto-Burman). A
comparison of the results presented here and the (minimally different) results of using
genealogically-weighted approaches are discussed in Appendix 4.


3. Results


We examine the results in detail for the world as a whole, and then in summary for
each of six macro-areas. Section 3.1 presents the global dimensions of variation, what
linguistic features characterise these dimensions, and where languages displaying the
highs and lows of these dimensions can be found.6 In Section 3.2 we examine the
dimension plots presented in Figure 3 to show where various areal or genealogical
entities can be found, and to what degree they form ‘compact’ clusters in typological
space. In Section 3.3 we examine whether, and to what extent, these feature groupings
can be considered universal, based on their appearance in the separate analyses of
individual macro-areas.


3.1. Overall


Figure 1 shows the percentage of total variance explained by each of the first 20
dimensions of the FAMD result, with the ‘elbow’ indicated by the arrow. As we can
see, there is a sharp drop-off on the scree plot after the first four dimensions; thus,
following principles in Cattell (1966), in the following we consider only the first four
dimensions.




6
    We present four dimensions of variation, for the reasons discussed in Section 2.


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Kalyan & Donohue                                                Dimensions of Morphosyntactic Variation




            Figure 1: Scree plot showing variance accounted for by the first 20 dimensions.


The positions of languages according to these four dimensions are plotted in Figure
3. The leftmost column shows Dimension 1 along the x axis, and Dimensions 2, 3 and
4 on the y axis in rows 2, 3 and 4, respectively. In the second column Dimension 2 is
shown on the x axis, and Dimension 1 is displayed on the y axis. In the third column
Dimension 3 is plotted on the x axis, and in the fourth column Dimension 4 is plotted
on the x axis, with the y axes representing the same dimensions as previously
described. The colours of the dots vary according to their positions on the first, second
and third dimensions, with these dimensions mapped to red, green and blue colour
components, respectively (a technique exemplified in Nerbonne 2009, and other
associated works). Combinations of red and green display as yellow, red + blue as
purple/magenta, red + green + blue as white. Green + blue is cyan, and the absence
of any colouring is black, as shown schematically in Figure 2 (dots can of course also
occupy positions inside the cube, where the display colour tends towards grey). Note
that in Figure 3 (and later in Map 12) Dimension 4 is not represented in the colours
displayed (though see Appendix 8). These four dimensions in total account for 22.2%
of the variance in the data (a figure comparable to, for example, Skirgård et al. 2023),
as shown in Table 2.7




7
    Much of the remaining data can be divided into a) rare features; b) wide-spread common features
without strong correlations with other grammatical features; c) geographically restricted features. This
is discussed in Section 4. Section 3.3 examines the contribution of other features in determining
variation in smaller regions (see also Appendix 5).


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Linguistic Typology at the Crossroads 3-2 (2023): 132-190


          Dimension                 Variance accounted for?                      Section
                1                              7.7%                               3.1.1
                2                              6.4%                               3.1.2
                3                              4.2%                               3.1.3
                4                              3.9%                               3.1.4


              Table 2: Variance in the data accounted for by the first four dimensions.




                         Figure 2: An illustration of a ‘Red-Green-Blue’ cube.


The interpretation of the different dimensions is presented in 3.1.1 – 3.1.4; in
summary, the top end of Dimension 1, shown in red and orange, indicates languages
with prepositions, and a tendency towards subject prefixes on verbs, while the bottom
end is occupied by SOV languages with case-marking, shown in green and blue. The
top end of Dimension 2 correlates with morphologically elaborate verbs, marked in
pale green, while the bottom end tends towards isolating languages, with magenta
colours. Dimension 3 has languages with gender systems and plural marking on nouns
at the top end; languages at this pole are generally brown, while the lower end of this
dimension correlates with VOS order and clusivity contrasts, presenting in a mix of
colours in Figure 3. The top of Dimension 4 correlates with VSO languages that have
prenominal modifiers in the NP, while the lower end correlates with SV order, object
prefixes on verbs, and noun-numeral orders. As noted above, the position of a
language on Dimension 4 is not indicated by any particular colours in Figure 3, but


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Kalyan & Donohue                                                Dimensions of Morphosyntactic Variation


Figures A8.1, A8.2 and A8.3, as well as Figures A8.6, A8.8 and A8.9 in Appendix 8
show the effects of having Dimension 4 contributing to the colouring.




             Figure 3: Languages plotted according to the first four dimensions of variance.


We can see that there are different ‘densities’ of languages in different areas in Figure
3, such as the paucity of languages at approximately (0, 3) in the plot of Dimension
1 vs. Dimension 4 (at the bottom left of Figure 3), and the high concentration of
languages at (–6, 2.5) in the plot of Dimension 1 vs. Dimension 2 (at the top left of
Figure 3).8 The dimension plots, based purely on linguistic features, include a number
of typologically differentiated or isolated regions that correspond with a high degree
of precision to geographically-recognisable areas or genealogically-coherent entities,
some of which are discussed below in 3.2 (and see Section 4 for further discussion).

8
    The low-density region corresponds to a mix of languages, including many from modern Iran such as
Farsi (pes; west2369, Indo-European, Iranian) and Sorani (ckb; cora1257, Indo-European, Iranian),
and the high-density region is occupied by the head-final languages displaying and extreme head-final
typology such as is found in Turkish, Daghestanian, and other languages from central Eurasia.


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Linguistic Typology at the Crossroads 3-2 (2023): 132-190


     In the following subsections, each dimension is characterised in terms of the
features that show the strongest association with it; in the case of binary variables,
the strength of this association is measured with an ANOVA test, and for continuous
variables, it is measured using Pearson correlation. In both cases, we report an r2
value. To determine whether the association is positive or negative, we look at the
sign of the correlation coefficient (for continuous variables), or (for binary variables)
perform a t-test comparing the dimension values of languages either exhibiting or
lacking the feature against the entire set of languages, and note which (if either) of
the two t-tests shows a significant positive value, and which (if either) shows a
significant negative value. In Maps 5 – 8 positive values are shown in red/brown, and
negative values in blue, according to the scale in Figure 4 (exact values can be found
in Appendix 1).




                                Figure 4: The scale used in Maps 5 – 8.


3.1.1 Dimension 1: order of object and verb


The features most strongly associated with the first dimension centre around the order
of the verb and its object, as well as a number of further headedness relations such as
the position of a marker of subordination, the presence of prepositions, and the
presence and position of case markers. Table 3 shows the features that have the
strongest associations with Dimension 1.9




9
    For display purposes a number of related features from our database have been merged in this and
subsequent tables for simplicity of presentation. For instance, both ‘SOV’ and ‘OV’ are associated
(negatively) with Dimension 1 (since languages with these features on average have a negative value
along Dimension 1; r2 = 0.53 and 0.54, respectively). They are reported in Table 3 simply as SOV.
Similarly, ‘Core case (any)’, ‘Dependent marking’, ‘Number of cases’ and ‘Postnominal case’ are all
associated (negatively) with Dimension 1 (r2 = 0.43, 0.49. 0.49 and 0.50, respectively), but only two
of these features are listed in Table 3. Fuller lists of r2 values are found in Appendix 1.


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Kalyan & Donohue                                          Dimensions of Morphosyntactic Variation


       Direction   Feature                                                            r2
       High        Prepositions                                                    0.50
                   Verb-Object order                                               0.42
                   Initial subordination                                           0.41
                   Nominative agreement by prefix                                  0.32
                   Obliques follow verb                                            0.31


                   Genitive precedes noun                                          0.31
                   Final subordination by suffix                                   0.39
                   Postpositions                                                   0.42
                   Obliques precede verb                                           0.45
                   Number of cases                                                 0.49
                   Postnominal case                                                0.50
       Low         SOV order                                                       0.53


               Table 3: Features characterising the extremities of Dimension 1.


These features are strongly reminiscent of (elements of) Greenberg’s (1963) discussion
of word order universals, and other linguistic features that refer to headedness
parameters at the clause level. It is notable that prepositions are more closely
associated with the positive (VO) end of this dimension than postpositions are with
its negative (OV) end, and that head-final languages are strongly associated with the
OV end, while head-initial languages are not as firmly associated with the VO end.
  In Map 5 we can see the languages in our sample coded according to their position
on Dimension 1, with high values marked in red/brown, and low values in blue, and
middling values showing little hue. There are clear areal trends in the distribution of
the extremes of this dimension, with large swathes of Eurasia dominated by languages
with low (OV-congruent) values, and most of sub-Saharan Africa and Island Southeast
Asia showing high (VO-congruent) values. Areas without consistent headedness
settings, such as most of western Europe or northern China, are not associated with
either extreme. The languages that are highest on Dimension 1 include various
Otomanguean languages of the Chinantecan, Zapotecan and Popolocan groups in
Central America, as well as Celebic Austronesian languages from central Indonesia,
such as Mori (xmz; mori1268), Wolio (wlo; woli1241) and Wotu (wtw; wotu1240).
The low end is dominated by South Asian languages, particularly South Dravidian




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(Tamil, Tulu and Toda)10 from the south of the subcontinent, and Bodic Tibeto-
Burman (Kurtöp, Ghale and Balti)11 from the Himalayas.




               Map 5: Position of languages on Dimension 1 (blue = low, brown = high).



3.1.2 Dimension 2: verbal elaboration


The 2nd dimension of variation concerns the amount of morphology that can appear
on the verb. At one end we have verbs with multiple positions for agreement, valency-
increasing morphology for Ps (and, to a lesser extent, As), noun incorporation, and
other inflectional material, such as switch-reference marking, Tense/Aspect/Mood,
evidentiality, pluractionality, polarity, honorificity, voice marking, etc. (Bickel and
Nichols 2013). At the other end, we find languages that lack extensive verbal
morphology. The features with the strongest associations involve the lack of
subordinating characteristics in “subordinate” clauses of different types, but the
absence of the features characteristic of the higher end of this dimension, as well as
the tendency for languages low on Dimension 2 to correlate with Dimension 1 (see
Figure 3, and see 3.4), means that these languages tend to be more isolating.




10
     Tamil (tam; tami1289); Tulu (tcy; tulu1258); Toda (tcx; toda1252).
11
     Kurtöp (xkz; kurt1248); Ghale (ghe; barp1238); Balti (bft; balt1258).


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           Direction      Feature                                                             r2
           High           Total verbal agreement positions                                 0.37
                          Total verbal inflectional synthesis                              0.34
                          Total Modality affixes                                           0.30
                          Incorporation                                                    0.22
                          Applicatives                                                     0.20
                          Causatives                                                       0.16
                          Possessive prefixes on nouns                                     0.15
                          Total tense distinctions                                         0.11


                          SVO order                                                        0.14
                          Symmetrical clauses: Purpose                                     0.17
                          Symmetrical clauses: Temporal                                    0.18
           Low            Symmetrical clauses: Reason                                      0.21


                     Table 4: Features characterising the extremities of Dimension 2.


The features here are strongly reminiscent of (and add to) the head-marking end of
Nichols’ (1986) typology of head-marking vs. dependent-marking languages (itself
related to divisions of morphological typology established as early as K.F. Schlegel
1808 and A.W. Schlegel 1818), with languages high on Dimension 2 being more
heavily head-marking, and languages low on Dimension 2 showing more
isolating/analytic traits. (We have already seen that dependent-marking is associated
with Dimension 1, specifically with its lower OV end.)
      In Map 6 we can see that the languages of the Americas are almost universally on
the head-marking side of this dimension; the opposite extreme, namely absence of
head-marking characteristics, dominates in Southeast Asia, to a lesser extent in
western Africa, and in small measure in western Europe. The Old World sees clusters
of head-marking languages in the Caucasus, in East Africa, in the Munda-Kiranti areas
of South Asia, in the north-east of Eurasia on the approach to the Americas; parts of
New Guinea, and most of northern Australia, also contain languages that are strongly
head-marking, and so high on Dimension 2. Languages from a number of families in
Southeast Asia are found at the low end of Dimension 2, including Austronesian
(Moken, Cham)12, Austroasiatic (Bruu, Vietnamese)13, and also Hmong and Thai
languages; a number of languages of West Africa, centred on Nigeria (such as Igede

12
     Moken (mwt; moke1242, Malayo-Sumbawan); Cham (cjm; east2563, Malayo-Sumbawan).
13
     Bruu (bru; east2332, Katuic); Vietnamese (vie; viet1252, Vietic).


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and Yoruba)14, are also high on this dimension. The higher end of the scale is occupied
by polysynthetic languages from North America (such as Algonquian Arapaho,
Cheyenne and Ottawa)15, from the North-west Caucasus family (including Abaza,
Adyghe and Kabardian)16, as well as Chukotko-Kamchatkan Alyutor (alr; alut1245),
and a number of western Amazonian languages from the South American (such as
Aikanã, Jebero, Matses, Arakmbut and Matsigenka)17, and a scattering of languages
elsewhere.




               Map 6: Position of languages on Dimension 2 (blue = low, brown = high).



3.1.3 Dimension 3: Western Old World


The third dimension of variation shows the strongest (macro-)areal distribution.
Unlike the other three dimensions discussed here, the distribution of Dimension 3
does not identify a number of separate areas throughout the world, but rather a global
cline from west to east (as is clearly visible in Map 7, and see below). The features at
the high end of this dimension are all morphological; at the low end we see either an
absence of extensive nominal morphology, or verb-initial orders. Because of these two

14
     Igede (ige; iged1239, Niger-Kongon, Idomoid); Yoruba (yor; yoru1245, Niger-Kongo, Yoruboid).
15
     Algonquian Arapaho (arp; arap1274); Cheyenne (chy; chey1247); Ottawa (otw; otta1242).
16
     Abaza (abq; abaz1241); Adyghe (ady; adyg1241); Kabardian (kbd; kaba1278).
17
     Aikanã (tba; aika1237, Isolate, Aikanån); Jebero (jeb; jebe1250, Cahuapanan); Matses (mcf;
mats1244, Panoan, Matses); Arakmbut (hug; arak1258, Harakmbet); Matsigenka (mcb, mach1267,
Arawak, Campa).


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different typologies, the r2 values of features at the low end of this dimension are not
as high as those at the high end.


       Direction                        Feature                                        r2
       High         Gender                                                          0.28
                    Obligatory plural marking on nouns                              0.27
                    3SG pronominal gender                                           0.25
                    Verb alignment: accusative                                      0.22
                    3PL pronominal gender                                           0.17
                    Suffixal subject agreement on verbs                             0.13
                    Relative pronouns                                               0.13


                    Ergativity                                                      0.13
                    VOS order                                                       0.15
                    Inclusive/Exclusive contrasts                                   0.18
       Low          Clause-initial negation                                         0.18


                Table 5: Features characterising the extremities of Dimension 3.


As can be seen in Map 7, languages low on this dimension are almost exclusively
found in the Circum-Pacific region, an area which “comprises all of the Americas,
Oceania (including Australia and New Guinea), and the mainland Asian Pacific Rim”,
the last area being the “Pacific-facing coast up to the lower slope of the far side of the
major coast range” (i.e., the eastern Himalayas) (Bickel & Nichols 2006: 6). We
observe increasingly high values as we go west in the Old World. On the high end we
find most of the languages of Europe and the other circum-Mediterranean languages,
as well as the Bantu languages, which have significantly higher values than those in
the rest of Eurasia and Africa (see 3.2.1 and 3.2.10). In part due to this position, and
the relative morphological simplicity of European languages compared to Semitic,
Berber or Bantu languages (thus having lower values on Dimension 2), the languages
of Europe can be identified as a global outlier (see Figure 3, and 3.2.1).




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             Map 7: Position of languages on Dimension 3 (blue = low, brown = high).


The features that have a strong association with Dimension 3 partially overlap with
the list of features often put forward as defining ‘Standard Average European’ (Whorf
1941, and also Haspelmath 2001, van der Auwera 2011, and others). Often-cited
‘Standard Average European’ features that have positive correlations with Dimension
3 include: indefinite articles, have-perfects, relative pronouns (see Table 5),
predominantly suffixing morphology (see Table 5), accusative alignment (see Table
5), and negative indefinite pronouns. Features that have negative associations with
Dimension 3 include clusivity contrasts (see Table 5), alienability contrasts, identity
of ‘and’ and ‘with’, and productive reduplication. In contrast to other studies on
Standard Average European, we find that dative subjects have a (weak) positive
association with Dimension 3 (r2 = 0.10). (See Appendix 1 for details of the
associations of these features with the different dimensions.)
   It is clear from Map 7 that Dimension 3 negatively correlates with ‘eastness’ (as
displayed on Map 7, such that Iceland is west and Greenland is east). The correlations
of the different dimensions with ‘eastness’ in different domains are shown in Table 6.
The strong negative correlation of Dimension 4 (3.1.4) with eastness in Eurasia
reflects the far western position of the verb-initial Celtic, Berber and Semitic
languages; there are very few verb-initial languages in the east of mainland Eurasia.




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Dimension 3, however, shows strong correlations across Eurasia, the Old World, and
globally.18


                    Dimension            Global         Old World            Eurasia
                         1                 -0.02              -0.11             -0.45
                         2                  0.36              -0.14             -0.22
                         3                 -0.54              -0.61             -0.74
                         4                 -0.21              -0.26             -0.73


                                  Table 6: Correlation with eastness (r).


The languages at the top end of Dimension 3 are Niger-Kongo Bantu (Ruwund,
KinyaRwanda and Runyankore)19, Indo-European Romance (Spanish, Romansch,
Galician and French)20 or Afro-Asiatic Semitic (Cypriot Arabic, Mlaḥsô and Fezzan
Arabic)21, in addition to a number of other European languages (such as Albanian,
Czech and Tabarchino)22. As can be seen in Figure 3, the lower end of Dimension 3 is
quite dispersed typologically, and consequently there is a range of different languages
that are maximally different from those of the western Old World, as measured on
this dimension. Languages at the bottom of Dimension 3 include verb-initial
Texistepec (poq; texi1237, Totozoquean, Chitimacha–Zoque), Kuikuro (kui;
kuik1246, Cariban, Nahukwa), Shuswap (shs; shus1248, Salishan, Interior Salish),
and many languages of the Philippines and Taiwan (such as Hanunoo, Saaroa and
Maranao)23, and Polynesia (Samoan and Niuean)24 in the Pacific. In addition to their
verb-initial clauses, these languages also lack gender in nouns or pronouns, accusative
alignment, or obligatory plural marking.



18
     Strong negative correlations are also found in South America (-0.41), due to the presence of a large
area in the northern Andean region occupied by languages with higher values on Dimension 3,
belonging to the Jivaroan, Quechuan, Tucanoan and Boran families, amongst others.
19
     Ruwund (rnd; ruun1238); KinyaRwanda (kin; kiny1244); Runyankore (nyn; nyan1307).
20
     Spanish (spa; stan1288), Romansh (roh; roma1326), Galician (glg; gali1258), French (fra; stan1290).
21
     Cypriot Arabic (acy; cypr1248); Mlaḥsô (lhs; mlah1239); Fezzan Arabic (ayl; liby1240).
22
     Albanian (als; tosk1239, Indo-European, Albanian), Czech (ces; czec1258, Indo-European, Slavic);
Tabarchino (lij; ligu1248, Indo-European, Romance).
23
     Hanunoo (hnn; hanu1241, Austronesian, Philippines); Saaroa (sxr; saar1237, Austronesian, Tsouic);
Maranao (mrw; mara1404, Austronesian, Philippines).
24
     Samoan (smo; samo1305, Austronesian, Oceanic); Niuean (niu; niue1239, Austronesian, Oceanic).


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3.1.4. Dimension 4: order of subject (and negator) and verb, and NP orders


The other major aspect of clausal word order, the order of subjects and predicates, is
found to have the strongest associations with both ends of Dimension 4. Clause-initial
negation, which is overwhelmingly (but not exclusively) associated with verb-initial
languages, also shows strong positive associations with Dimension 4. Unlike the word
order correlations evident in Dimension 1, a number of NP-internal correlations are
found with Dimension 4, leading to a number of languages which are not verb-initial
nonetheless displaying high values on this dimension.


         Direction     Feature                                                          r2
         High          VSO order                                                      0.22
                       Clause-initial negation                                        0.20
                       Numeral precedes noun                                          0.19
                       Clause-initial Wh-question words                               0.11
                       Adjective precedes noun                                        0.11
                       Genitive precedes noun                                         0.10
                       Relative pronouns                                              0.10


                       Clause-final negation                                          0.10
                       Inalienable possession                                         0.10
                       Object agreement prefix                                        0.14
                       Numeral follows noun                                           0.14
         Low           SV order                                                       0.21


                   Table 7: Features characterising the extremities of Dimension 4.


The order of subject and verb again reflects Greenberg’s classification of the world’s
languages by clausal word order. As with the order of object and verb, seen in Map
5, we can identify a number of contiguous areas which are high or low on this
dimension. The relative paucity of VS languages, compared to SV languages, means
that it is easiest to consider the distribution of these languages compared to a
background of SV languages. The languages at the top of Dimension 4 are mostly
Semitic and Berber languages from north Africa and the Middle East, and the Celtic
languages of western Europe, though certain south-eastern Australian languages such
as Warrnambool (gjm; warr1257, Pama-Nyungan, Kulinic), Wembawemba (xww;
wemb1241, Pama-Nyungan, Kulinic) and Muk-Thang (Garnai) (unn; gana1278,



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Pama-Nyungan, Gippsland) are also found at this extreme. Languages at the opposite
extreme of this dimension are found in North America, including the Athabaskan
languages Dena’ina (tfn; tana1289), Kaska (kkz; kask1239) and Slavey (xsl;
sout2959), and the Siouan languages Lakhota (lkt; lako1247), Stoney (sto; 1ton1242),
Hidatsa (hid; hida1246) and Hocąk (Winnebago) (win; hoch1243), as well as in
languages from various families on the fringes of New Guinea, such as Puare (pux;
puar1240) and Barupu (wra; wara1302) (Skou family); Riantana (ran; rian1263,
(Trans   New       Guinea?),   Kolopom),     and    the    Timor-Alor-Pantar         languages
Tanglapui/Sawila (tpg; sawi1256), Lamma/Western Pantar (lev; lamm1241), Adang
(adn; adan1251), Abui (abz; abui1241) and Kamang (woi; kama1365).




           Map 8: Position of languages on Dimension 4 (blue = low, brown = high).


3.2. Geographically or genealogically recognisable regions


In this section we return to the dimension plots seen in Figure 3 (and compare also
with Map 12), and examine recognisable geographic or genealogical regions to
determine whether, and to what extent, they correspond to distinct ‘regions’ in
typological space. To assess whether a given geographic or genealogical group
clusters on one side of a given dimension, we perform a one-sided t-test comparing
the values of languages within the group along that dimension, and the values of all
languages in the dataset along that dimension. Generally, t values greater than 20 or
less than –20 indicate that a group of languages shows extreme values along a given
dimension, and/or forms a tight cluster along that dimension. A p-value close to zero


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indicates that the means of the two populations being compared are significantly
different; however, since p values are generally lower for larger datasets, the results
should be interpreted on the basis of the t statistic as well as the p value. We also
report the degrees of freedom (df) for each analysis.


3.2.1. Western Old World: Europe, Arabia and North Africa


As mentioned in 3.1.3, the languages of (western) Europe almost all occupy a position
high on Dimension 3 (Western Old World) (t = 40.24, df = 178.89, p < 0.001,
according to a one-sided t-test) and 4 (‘order of subject (and negator) and verb, and
NP orders’), and moderately low on Dimension 2 (‘verbal elaboration’) (t = –14.39,
df = 175.57, p < 0.001). The region of typological space that can be seen in the
combination of these two dimensions is quite separate from the rest of the cloud;
exceptions to this separation, found much lower on Dimension 3, are recognised as
outliers within Europe: Basque varieties (eus; basq1248), Hungarian (hun;
hung1274), Gagauz Turkish (gag; gaga1249), and (to a lesser extent) the Celtic
languages. The mixed word-order typology of most of the European languages (with
head-initial parameters dominating at the clause level, and head-final parameters
predominant within NPs) means they occupy a position in the middle of Dimension 1
(‘order of object and verb’), and they can be seen to occupy a distinct, albeit interior,
position in the plot of Dimension 1 vs. Dimension 2. In Figure 4 we can see that the
languages of Europe occupy a compact region in typological space in each of the
dimension plots, including those that do not involve dimensions 2 or 3, though they
are not part of the ‘fringe’ of typological space.
   Figure 5 shows the position of the languages of Arabia and North Africa; not as
compact as the European languages, they can also be characterised as occupying a
fringe positions on the plot of Dimensions 1 and 3 (t = 20.49, df = 52.25, p < 0.001;
t = 18.38, df = 49.89, p < 0.001), and are higher on Dimension 1 than the European
languages (t = 18.42, df = 73.60, p < 0.001), but not significantly higher on
Dimension 4 (two-sided t = 0.92, df = 53.17, p = 0.36). The outliers at the lower
end of Dimension 3 for this group of languages are mixed languages in the areas, such
as Kumzari (zum; kumz1235, Indo-European (?), Iranian), between Arabia and Persia,
and Kwarandzyey (/Korandje) (kcy; kora1291), a Songhai language spoken in the
extreme north-east of the Sahara in a Berber linguistic environment.




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               Figure 5: Languages of Europe highlighted on the dimension plots.




       Figure 6: Languages of Arabia and North Africa highlighted on the dimension plots.




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3.2.2. Mainland Southeast Asia


The languages of Southeast Asia represent a number of typologically convergent
language families, all low on Dimensions 2 and 3 (t = –41.17, df = 366.98, p <
0.001; t = –30.25, df = 821.84, p < 0.001). The outliers for this group, typologically,
are also outliers geographically. The most divergent languages are the Nungish
languages of northern Myanmar and adjacent China, high on Dimension 2, and the
Nicobarese languages of the Nicobar Islands, high on Dimension 4 (raising questions
about their inclusion in a ‘Mainland Southeast Asia’ area). As with the languages of
Europe, the languages of Southeast Asia largely cluster together even in plots that do
not involve Dimension 2 or Dimension 3.




        Figure 7: Languages of mainland Southeast Asia highlighted on the dimension plots.


3.2.3. Core South Asia


The Indic (< Indo-European) and Dravidian languages of South Asia also cluster
together, though not at the periphery of any of plots, except for their low position on



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Dimension 1 (t = –41.99, df = 205.58, p < 0.001), and relatively high position on
Dimension 3 (t = 29.02, df = 136.18, p < 0.001). The typological outliers for this
area, low on Dimension 3 or high on Dimension 1, are Vedda (ved; vedd1240, Indo-
European, Indic), from Sri Lanka, and Dari (prs; dari1249, Indo-European, Iranian),
the eastern variety of Farsi spoken in Afghanistan and not typologically assimilated
to the languages of the region.




           Figure 8: Languages of ‘core South Asia’ highlighted on the dimension plots.


3.2.4. Inner Asia


The core Eurasian profile of a radically head-final language (low on Dimension 1: t
= –25.13, df = 191.91, p < 0.001) with a modest level of morphological elaboration
(moderately greater than zero on Dimension 2: t = 4.52, df = 165.25, p < 0.001) is
most strongly realised in Inner Asia, where Mongolic, Tungusic, Turkic and Uralic
languages share many typological features. The outliers in this group are recently-




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arrived varieties of Mandarin (Dungan, Urumqi and Taz)25 and Arabic (Afghanistani
Arabic and Bukhara Arabic)26, which are low on Dimension 2 and high on Dimension
1, respectively.




                  Figure 9: Languages of Inner Asia highlighted on the dimension plots.


3.2.5. North America


The languages of North America are widely dispersed, though the average position,
and densest grouping, is both high on Dimension 2 (t = 24.8, df = 406.47, p <
0.001) and low on Dimension 3 (t = –17.3, df = 428.62, p < 0.001), indicating a
head-marking, morphologically complex language that is maximally different from
the languages of western Eurasia. In Dimension 1 and Dimension 4 there is no
apparent pattern (two-sided t = –0.94, df = 322.14, p = 0.35), but in Dimension 1
the languages on average have values slightly greater than zero (t = 6.60, df =
339.84, p < 0.001).

25
     Dungan (dng; dung1253); Urumqi (cmn; wulu1243); Taz (cmn; north3283).
26
     Afghanistani Arabic (abh; taji1248); Bukhara Arabic (auz; uzbe1248).


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          Figure 10: Languages of North America highlighted on the dimension plots.


3.2.6. Mesoamerica




           Figure 11: Languages of Mesoamerica highlighted on the dimension plots.


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Focussing just on the languages of Mesoamerica as a sub-region within North America
we find a high degree of typological dispersal, but with a cluster high on Dimension
1 (t = 8.63, df = 86.28, p < 0.001) and middling high on Dimension 4 (t = 6.81, df
= 89.38, p < 0.001).


3.2.7. The Philippines and Taiwan


The ‘Philippine-type languages’ of the Philippines and Taiwan, which, while mostly
Austronesian, do not form a valid subgroup within that family, can be found high on
Dimension 4 (t = 31.15, df = 56.38, p < 0.001) and low on Dimension 3 (t = –7.88,
df = 64.48, p < 0.001), where they form a fringe to typological space.




      Figure 12: Languages of the Philippines and Taiwan highlighted on the dimension plots.


In other dimension plots they also form a tight cluster, with the divergent languages
from this region (high or low on Dimension 2, or low on Dimension 1 or 4) being 1)
the Austronesian languages of Taiwan (high on Dimension 2), 2) Iraya (iry; iray1237,
Austronesian) from Mindoro in the Philippines, and Taiwanese (nan; taib1242,
Tibeto-Burman, Sinitic), the intrusive Sinitic language of Taiwan (low on Dimension 2),




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and 3) the southern Austronesian languages in this cluster, such as Talaud (tld; tala1285)
and Sangir (sxn; sang1336) from northern Indonesia (low on Dimensions 1 and 4).


3.2.8. Eskimo-Aleut


The languages of the Eskimo-Aleut family are very low on both Dimension 1
(t = –15.51, df = 15.79, p < 0.001) and very high on Dimension 2 (t = 39.45, df =
16.29, p < 0.001), indicating a morphologically elaborate group of extremely SOV
languages. As a small and young family they form a tight cluster, and represent an
extreme extension of the North American (or North-east Asian) linguistic type.




       Figure 13: Languages of the Eskimo-Aleut family highlighted on the dimension plots.


3.2.9. North-west Caucasus


The languages of the North-west Caucasus family occupy a position similar to the
Eskimo-Aleut languages, but more extreme (Dimension 1: t = 5.24, df = 8.01, p <
0.001; Dimension 2: t = 5.47, df = 7.88, p < 0.001).




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        Figure 14: Languages of the Eskimo-Aleut family highlighted on the dimension plots.


3.2.10. Narrow Bantu




      Figure 15: Languages of the Narrow Bantu subgroup highlighted on the dimension plots.



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The many languages of the Narrow Bantu subgroup, found in a broad, contiguous
range across southern Africa, are highly typologically congruent, being found high on
Dimensions 1 and 3 (t = 50.14, df = 587.47, p < 0.001; t = 51.67, df = 318.28, p
< 0.001), and low on Dimension 4 (t = –12.09, df = 518.94, p < 0.001). They
represent a typological extension away from the rest of the language cloud, seen in
the plot of Dimension 3 vs. Dimension 4. Typological outliers of this group (lower on
Dimension 2, or lower on Dimension 3) include the peripheral Bantu languages from
the north-west of the Bantu expanse, in Cameroon, The Congo, or the Democratic
Republic of the Congo, which are more isolating than the ‘modal’ Bantu language.


3.2.11. Greater Abyssinia


The languages of Greater Abyssinia, centred around the Horn of Africa, are
typologically diverse, but are all relatively higher on Dimensions 2 (t = 5.25, df =
105.57, p < 0.001), and lower on Dimension 3 (t = –5.77, df = 84.27, p < 0.001),
than the Bantu languages.




         Figure 16: Languages of Greater Abyssinia highlighted on the dimension plots.



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3.2.12. Pacific North-west


The languages of the Pacific North-west are typologically convergent languages from
a number of families, high on Dimension 2 (t = 17.36, df = 31.86, p < 0.001), low
on Dimension 3 (t = –14.24, df = 30.02, p < 0.001), and high on Dimension 4 (t =
8.30, df = 29.04, p < 0.001). The outliers lower on Dimensions 1 or 4 are at the
northern or southern edges of the area (Tlingit (tli; tlin1245, Na-Dene, Tlingit) and
Haida (hdn; nort2938, Haida), Klamath (kla; klam1254, Klamath-Modoc), Kalapuya
(kyl; kala1400, Kalapuyan) and Molala (mbe; mola1238), respectively).




         Figure 17: Languages of the Pacific North-west highlighted on the dimension plots.


3.2.13. Southern and Central Australia


The Pama-Nyungan languages of southern and central Australia occupy a small region
of typological space which is low on Dimensions 1, 3, and 4 (t = –27.94, df = 207.27,
p < 0.001; t = –23.40, df = 183.71, p < 0.001; t = 15.38, df = 158.29, p < 0.001),
and in the middle of Dimension 2 (two-sided t = –1.06, df = 182.96, p = 0.29).


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Languages higher on Dimension 2 are those which have some form of agreement, on
the very or via clitics, and languages higher on Dimension 4 tend to be found in the
south-east of the continent.




    Figure 18: Languages of southern and central Australia highlighted on the dimension plots.


3.2.14. North-east Asia


The languages of North-east Asia, comprising the Ainu and Chukotko-Kamchatkan
language families, as well as the Tungusic languages north of Hokkaido and the
Eskimo-Aleut languages spoken west of the Bering Strait, and the Yukaghir languages.
These languages are all high on Dimension 2 (t = 11.59, df = 17.85, p < 0.001), but
do not occupy a typologically compact space in terms of the other three dimensions
examined here (Dimension 1: two-sided t = –2.28, df = 17.27, p = 0.035; Dimension
3: two-sided t = –1.08, df = 17.36, p = 0.29; Dimension 4: two-sided t = –0.54, df
= 17.28, p = 0.59).




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            Figure 19: Languages of North-east Asia highlighted on the dimension plots.


3.2.15. Andes


The languages of the Andes are for the most part quite compact; exceptions are the
isolates Camsá (kbh; cams1241), Esmeraldeño (atac1235), and Cholon (cht;
chol1284), and to a lesser extent the Chibchan language Kuna (kvn; sanb1242), all in
the north of the region except for Cholon, in Pre-Andine Peru. The main group of
Andean languages, from the Aymaran, Barbacoan, Chocoan, Jivaroan and Quechuan
families, are low on Dimension 1 (t = –13.75, df = 45.60, p < 0.001) and high on
Dimension 2 (t = 12.13, df = 44.46, p < 0.001), and occupy middle positions on
Dimensions 3 and 4 (t = 2.80, df = 51.54, p < 0.01; two-sided t = 2.30, df = 44.66,
p = 0.026).




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          Figure 20: Languages of the Andes family highlighted on the dimension plots.


3.2.16. Mamoré–Guaporé




  Figure 21: Languages of the Mamoré–Guaporé area family highlighted on the dimension plots.


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The languages of the Mamoré–Guaporé area are typologically diverse in terms of the
global dimensions of variation. In an analysis restricted to just South America these
languages emerge as distinct, reflecting the widespread use of prefixal agreement and
possessive affixes in these VO languages. As with other languages of the Americas,
these languages are low on Dimension 3 (t = –8.18, df = 37.66, p < 0.001).


3.3. Universality? Macro-areas examined


In this section we examine whether the features that characterise the dimensions
described in 3.1 are also relevant within individual macro-areas, paralleling the
methodology advocated by Dryer (1989, and subsequent publications) that seeks
confirmation for universals by their universal, independent attestation around the
world. We have already seen (3.2.5) that the languages of North America occupy a
position that does not cover the full extent of the dimensions, but in many dimensions
does occupy the fringe, suggesting that the parameters of variation within this macro-
area will be different, in at least some respects, from those that pertain to the globe
as a whole.27 In this section we report in outline the results of applying FAMD to
individual macro-areas.28 Tables 8 – 11 show the features that were discussed for each
of the global dimensions of variation that were described in 3.1, with each row
corresponding to a different macro-area, indicating, for each feature of the global
FAMD, which dimensions (if any) of the local macro-area show associations with that
feature (if any). For example, the difference between dominant OV vs VO order, a
feature associated with Dimension 1 in the global analysis (3.1.1), appears in
Dimension 1 in Africa, Eurasia, North America, the Pacific, and South America, but
is relegated to Dimension 2 in Australia, where word order is less dominant a variable;
in Africa VO order is also a feature with a strong association with Dimension 4. Case
marking, also a feature of (global) Dimension 1 in 3.1.1, appears in Dimension 1 in
all of the macro-areas except North America, where it is only found in the third
dimension. In Eurasia case marking is associated with both the first and second

27
     In Appendix 6 similar plots are given to show the distribution of the languages of the other macro-
areas in terms of the global variation.
28
     Note that the individual analyses result in different numbers of relevant dimensions, following the
methodology described in section 2. For Africa eight dimensions emerged as relevant (though just the
first two are sufficient to account for the variance in most of the languages); Eurasia, Australia and
South America require four dimensions each, and for the Pacific and North American macro-areas
three dimensions are optimal.


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dimensions, indicating its importance in that continent. Gender, a correlate of
Dimension 3 in the global analysis, appears in Dimension 1 in Africa, Eurasia and
Australia, but is not correlated with any of the major dimensions in the Pacific or the
Americas because of its rarity in those areas.
  Importantly, most of the features we encountered in the global analysis are also
relevant in (most of) the individual macro-areas, though their representation is
increasingly scattered in the higher dimensions. As mentioned above, the order of
object and verb is relevant in all macro-areas, though less prominently in Australia
than in other areas; dependent-marking is relevant in five macro-areas, though less
so in North America than in others. Agreement appears in the first two dimensions in
all macro-areas, and the order of subject and verb is relevant to different degrees in
all of the macro-areas; the scarcity of verb-initial languages in Africa and Eurasia
lowers the relevance of this feature in the Old World. The different valency-adding
devices (causatives and applicatives), which show a similarity to agreement in that
they encode argument information on the verb, are generally less prominent in
individual macro-areas, but are still relevant. The features associated with Dimension
3 globally are much less well-attested in individual macro-areas; this is to be expected,
since, as we saw in 3.1.3, this dimension essentially presents as a cline across the Old
World, and so is much less prominent from analyses of variation in the languages of
Australia, the Pacific or the New World. Nonetheless, these languages from the
western edge of the populated world are typological outliers, as seen earlier in Figure
3, in contrast to most of the languages of the Circum-Pacific region, and so this
dimension must be part of a global investigation.
                                                                                                              (Agreementsuffix)
                                                                                         Agreementprefix
                                          subordination




                                                                                                                                  Obl V / V Obl


                                                                                                                                                  Postpositions
                                                                          Prepositions
                                                          Initial/final




                                                                                                                                                                  Total cases
                         OV / VO


                                   Case




      Features
      Africa            1,4        1                                       1             1,2                  1,3                  1               1              1
      Eurasia            1         1,2                     1               1              3                                        1                              2
      Pacific            1         1                       1               1              2                                        1               1
      Australia          2         1                       4                              1                    2
      North America      1         3                       1               1              3                    3                   1               1              3
      South America      1         1                       1                              1                    2                   1               1


        Table 8: Features associated with Dimension 1, and their positions in macro-areal analyses.



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                                                                                                 Incorporation




                                                                                                                                                                                                                                    Symmetrical
                                                                                                                              Applicatives




                                                                                                                                                                                              Total tenses
                                                                                                                                             Causatives
                          agreement




                                                                                                                                                                     Possessive




                                                                                                                                                                                                                        SVO order
                                              synthesis




                                                                                    Modality




                                                                                                                                                          prefixes
                                                          Verbal
                                                                   affixes
                                      Total
      Features
      Africa                   1,2,7                      2                         2            4,5                           6             2,4                     7                         8                        1           2
      Eurasia                    2,3                      2                         1             4                      3,4                 2                                                 2                        2           2
      Pacific                    2,3                      1                         1                                          3                                     3                         1                        1           1,2
      Australia                1,3,4                      1                                      1,4                           3             3                                                 3
      North America              2,3                                                              2                            2             2                       3
      South America              1,3                                                                                           2             2                       1                         1                        1           3,4


               Table 9: Features associated with Dimension 2, and their positions in macro-areal analyses.
                                                                   plural marking




                                                                                                 Agreementsuffix
                                                                                    Obligatory




                                                                                                                                                                     VOS order
                                                                                                                                             Ergativity
                                                                                                                   pronouns




                                                                                                                                                                                  contrasts
                                                                                                                                                                                              Clusivity
                                                                                                                                                                                                             negation
                                                                                                                              Relative
                                                          Gender




                                                                                                                                                                                                                        Initial
                Features
                Africa                                    1                         1             1                      4,5                 6,8                3,4                      3,6                            3
                Eurasia                                   1                         1             1                      1,3                 1,2                                                                        1
                Pacific                                                                           1                                                                  1                         1                        2
                Australia                                 1                         1             2                                          1,4                     2                                                  2
                North America                                                       2                                                        1                       1                                                  1
                South America                                                 3,4                 1                                                                                            3                        2


                   Table 10: Features associated with Dimension 3, and their positions in macro-areal
                                                                                                 analyses.


In summary, most of the groupings of features we identified in 3.1 can be justified in
the context of the analysis of individual macro-areas, suggesting that these
associations between features are likely to arise from universal properties of human
language.
      The following sections briefly discuss the features that appear in the FAMD
analyses of individual macro-areas, including those which are not present in the
global analysis.29


29
     A more detailed explication of the FAMD analysis of the individual macro-areas is shown in Appendix
5.


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                                                                                                      Final negation
                                                                  Gen/Adj/Num




                                                                                                                       Inalienability
                                                  VSO order




                                                                                pronouns
                             negation




                                                                                                                                                SV order
                                                                                           Relative




                                                                                                                                        N Num
                                        Initial




                                                              N
             Features
             Africa                     3         3,6                                 4,5              2                                7       1,3
             Eurasia                    1         1                                   1,3                               3                       1
             Pacific                    2         2                                                                     1                       2
             Australia                  2         2                                                                     1                       2
             North America              1         1                                                    3                                1       1
             South America              2         2                                                    2               3,1              2       2


                Table 11: Features associated with Dimension 4, and their positions in macro-areal
                                                              analyses.


3.3.1. Africa


We can see in Table 12 that most of the features that determine variation within
Africa are consistent with the parameters of global variation.30 The differences that
can be found involve the strong correlation of postpositions with SOV languages in
Africa, which is not found globally, and the widespread use of prefixal plural marking,
which is so common amongst the Bantu and other Niger-Congo languages that it plays
a large role in the continent as a whole. In the fourth dimension, varieties of Malagasy
(bhr; bara1369) are differentiated by the nature of its voice system (here dubbed
‘superapplicative’, following Naylor 1995), and in the fifth and sixth dimensions,
which are justified following the same procedures described in Section 2, we find
features that identify certain Chadic and South Semitic languages which display
infixation, and a small number of mostly East Sudanic languages which have ergative
patterns.31




30
     Note that, as discussed in Section 2, we consider the languages of northern Africa, north of the
Sahara, to be part of the macro-area Eurasia, rather than Africa, for the reasons outlined there. As such
Arabic and Berber languages are not included in the analysis of Africa separate from Eurasia.
31
     Dimensions 2 and 3 correspond very closely to Dimension 2 (3.1.2) and Dimension 4 (3.1.4) from
the global analysis.


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    Dimension        Low                                                                         High
          1          SVO        Agreement prefixes                              Plural           SOV,
                                                                              suffixes   Postpositions
          2          Negative                                                  Verbal       Causatives
                     particle                                              agreement
          3          Subject-Predicate      Gender                                   Predicate-Subject
          4          ‘Superapplicative’     Double causatives, VOS,                      Head marking
                                            Incorporation
          5          Noun-modifier orders                                 Incorporatio         Infixes
                                                                                     n
          6          Gender in 1/2 pronouns                               Applicatives      Ergativity
          7          Incorporation       Possessive                         Double   Third agreement
                                         suffixes                         negation            position
          8          Possessive      Third agreement                       VSO order        Ergativity
                     classes         position


                                   Table 12: Relevant features: Africa.
              ‘Low’: features showing a negative correlation with the relevant dimension;
              ‘High’: features showing a positive correlation with the relevant dimension.


3.3.2. Australia


Australia is most at variance with global norms in terms of morphosyntactic variation.
As seen above, word order is not a correlate of the first dimension of variation in
Australia (though it is represented in the second dimension). The features correlating
with the major dimension of variation in Australia correspond to the long-discussed
Pama-Nyungan/non-Pama-Nyungan divide, with the north(-west)ern non-Pama-
Nyungan languages displaying prefixal agreement on verbs, often with portmanteau
subject/object morphemes, clusivity contrasts in bound morphology, and gender
systems. Opposing this are the Pama-Nyungan languages that occupy most of the
continent, which tend to be more dependent-marking, with ergative case marking,
and typically lacking gender contrasts. The second dimension picks out languages,
typically in the south-east of the continent, which are verb-initial and which employ
pronominal bases to which a productive affix is added (Daniel 2013).




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Kalyan & Donohue                                               Dimensions of Morphosyntactic Variation


   Dimension       Low                                                                         High
         1         Ergativity        Suffixing                              Gender,          Prefixal
                                                                           Clusivity       agreement
         2         SOV order                                    Pronominal bases           VOS order
         3         Verb agreement                                         Causatives     Applicatives
         4         Verb              Subordinating                  Incorporation        N Dem order
                   agreement         suffixes


                                Table 13: Relevant features: Australia.


3.3.3. Eurasia


As with Africa, the mapping of Eurasia in Section 4 reveals a number of clearly
separated areas. Unique features associated with dimension 1 include the contrast
between isolating languages and tense-marking languages. The second dimension has
a strong east-west distribution, with high values in the west, where word order is
manipulated to form content questions, and relative pronouns are used as
subordinators.


   Dimension       Low                                                                         High
         1         Tense, SOV        Case marking                                VO         Isolating
         2         Prenominal                                  Initial Wh-, subject          Relative
                   relative clause                                suffixes, gender          pronouns
         3         Accusative pronouns                                    Applicatives       Prefixal
                                                                                           agreement
         4         VS                                                                             SV
         5         Causatives                                                              Ergativity


                                Table 14: Relevant features: Eurasia.


3.3.4. Pacific


In the Pacific we again see an OV vs. VO divide along the first dimension, correlating
with suffixal subject morphology amongst the ‘OV Papuan’ languages and clusivity
contrasts in the VO Austronesian languages. The second dimension introduces prefixal
agreement as a major correlate.




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    Dimension     Low                                                                              High
          1       SOV         Subject agreement suffixes                     SVO      Clusivity contrasts
          2       Prefixal agreement        SV                  Initial negation, VS      Case marking
          3                                                  Applicatives, total agreement positions


                                  Table 15: Relevant features: Pacific.


3.3.5. North America


Most of the features that appear in the analysis of North America are also present in
the global analysis. Additionally, the second dimension distinguishes between
prefixing and suffixing languages.


Dimension      Low                                                                                    High
      1        SOV                                                        Negator-verb       Verb-predicate
      2        Suffixing      Causatives                                  Prefixal agreement      Prefixing
      3        Applicatives      Total agreement positions


                              Table 16: Relevant features: North America.


3.3.6. South America


Dimension      Low                                                                                    High
      1        SOV         Case marking                                    Prefixal     Prefixal possession
                                                                      agreement
      2        Symmetrical                                                 Suffixal            Applicatives
                                                              possession, object
                                                                      agreement
      3        Double       Clusivity in bound morphology       Verb agreement                   Causatives
               negation
      4        Modality affixes     Tense                         Suffixes plural           Initial question
                                                                          marking                  particles
      5        Applicatives                                                                   Dem N order


 Table 17: Relevant features: South America.‘Low’: features showing negative associations with the
  relevant dimension; ‘High’: features showing a positive association with the relevant dimension.




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South America shows the same VO vs. OV divide in the first dimension, but with less
clear areality than is seen in other macro-areas. There is a strong Andean area defined
by Dimension 2, abutting a Pre-Andine area defined by Dimension 3.


3.4. Correlations between dimensions?


By definition the different dimensions are as independent of each other as possible.
Table 18 shows the overall correlations that can be found between the different
dimensions; none of these correlations are significant, as shown in Table 18.


                    Dimension              1               2                3
                   1
                   2               0.034
                   3               0.021           0.025
                   4               0.001           0.023            0.020


   Table 18: Overall correlations between dimensions (r2; negative correlations shown in italics).


Despite the different dimensions being overall independent, some correspondence is
inevitable due to the presence of the same or similar features in more than one
dimension.




                         Figure 22: Dimension 3 (x) and Dimension 4 (y).



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More interestingly, some dimensions correlate with others in just part of their range.
Most dramatically, while there is only minimal correlation between Dimension 3 and
Dimension 4 (r2 = 0.020), the plot showing these two dimensions together (Figure
22, from Figure 3) shows clearly that at the lower half of Dimension 3 (on the left)
there is a negative correlation with Dimension 4 (r2 = 0.290), while at the upper half
of Dimension 3 (on the right) there is a positive correlation with Dimension 4 (r2 =
0.258). This reflects a split in the typology of verb-initial languages depending on
whether they are found in the west (Celtic, Semitic) or the east (Philippines, Central
America), since these languages are not typologically uniform. There is a weak
positive correlation between Dimensions 1 and 4 in the upper half of Dimension 1 (r2
= 0.064), reflecting the rarity of languages that are both OV and VS in their word
order. We find a slightly higher positive correlation with Dimension 2 at the bottom
tail (that is, for those values more than one standard deviation below the mean) of
Dimension 1 (r2 = 0.094); this corresponds to the fact that the very bottom of
Dimension 1 is occupied by languages from the Himalayas (which are both low on
Dimension 1, and concentrated in central Eurasia), which are less morphologically
elaborate than many less ‘extreme’ SOV languages, and moving away from this edge
almost inevitably leads to greater morphological elaboration, higher on Dimension 2.
The lower half of Dimension 2 shows positive correlations with both Dimension 3 (r2
= 0.205 in the extreme bottom) and Dimension 4 (r2 = 0.153 in the lower half).
These correlations largely reflect the position of the languages of Europe, high in
Dimension 3 and Dimension 4, but in the lower half of Dimension 2. The last
correlation we draw attention to is the lower half of Dimension 4, where we find a
weak positive correlation with Dimension 3 (r2 = 0.085) (see Figure 22).


4. Features with minimal contribution to global linguistic variation


In Section 3 we discussed the features that contribute to the dimensions that best
describe global (and regional) morphosyntactic variation. This section briefly
discusses some of the features that have the least contribution to global variation,
either because they are so rare, they have a very limited distribution, or they appear
in so many languages with little or no association with other parts of the language (at
least, as far as is coded in the database used). Some of these features are listed in
Table 19, which is not intended to be exhaustive.




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Kalyan & Donohue                                                  Dimensions of Morphosyntactic Variation


              Extremely Rare              Geographically                Widely Ubiquitous
                                              Limited
       Polar questions formed by          Genitive subjects         Predicative possession with a
            verbal reduplication                                   ‘have’ verb, or genitive subject
       More than three agreement          Polar questions            Polar questions forms with
            positions on the verb         forms with word              particles or intonation
                                           order change
           Marked absolutive case        Verb agreement by           Adnominal demonstrative
                                                tone                   identical to pronominal
                                                                           demonstratives
       Incorporation of transitive        Philippine-type          Presence of a perfective in the
             subjects into verbs           voice systems                    aspect system


      Table 19: Different features with minimal contribution to global categories of variation.


Examples of some of the ‘extremely rare’ features are shown in (4) – (7); in Yao’an
Lolo (ycl; lolo1259, Tibeto-Burman, Lolo-Burmese; Merrifield 2010) the only marker
of the question is the reduplication of the verb (the only language in our database
with this feature). In KinyaRwanda (Kimenyi 1980) we see a verb with five agreement
positions filled on the verb; the database contains only 12 languages with more than
three agreement positions. The Nias (nia; nias1242, Austronesian, Batak-Barrier
Islands; Donohue and Brown 1999, Brown 2005, Donohue 2008) sentences show the
alternation of the unmarked ulö ‘snake’ in an A function, and the marked g-ulö ‘snake’
in absolutive functions; sixteen other languages in the database have marked
absolutive cases, most (11) of which also mark the ergative role. In Boni (/Aweer)
(orm; awee1242, Afro-Asiatic, Cushitic, Omo-Tana; Sasse 1984) we see the rare case
of an incorporated A (Sasse notes that while a natural translation involves the passive,
the verbform in (7) is clearly transitive); only three other languages are known to us
with this feature.


(4)   Yao’an Lolo: reduplication on verbs marking polar questions
      Ni          pia          cir-cir            ho        ar?
      2SG         clothes      wash-RED           REAL      PFV

      ‘Have you already washed the clothes?’




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(5)     Kinyarwanda: more than three agreement positions
        Abáana ba-zaa-ha-ki-mu-b-eerek-er-a.
        children they-FUT-there-it-him-them-show-BEN-ASP
        ‘The children will show it to him for them there.’


(6)     Nias: marked absolutive case


a.      I-usu                  g-ulö              asu hö'ö.
        3SG.ERG-bite           ABS-snake          dog DIST
        ‘That dog bit the snake.’
b.      I-usu                  n-asu ulö          hö'ö.
        3SG.ERG-bite           ABS-dog            snake     DIST

        ‘That snake bit the dog.’
c.      Möi        ga          g-ulö.
        go         here        ABS-snake

        ‘The snake came this way.’


(7)     Boni: incorporated transitive subject
        Míŋ        ąwęęrą      kawáyd’aadéed’i idohóo^d’isa.
        house      Boni/GEN usually                 women^build/IMPERF/3SG.M
        ‘Boni houses are usually built by women.’




                            Map 9: Languages with extremely rare features.
     Blue = more than three agreement positions; Red = marked absolutive case; Purple = both the
                 preceding features; Black = polar questions marked by reduplication.




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Kalyan & Donohue                                          Dimensions of Morphosyntactic Variation


The distributions of languages displaying the first three of these features are shown
in Map 9, where red indicates languages with marked absolutives, blue indicates
languages with more than three agreement positions on the verb (compare with Map
1, which shows the total sample examined).
  Examples of features that are more common than those shown in Map 9, but which
have strong geographic concentrations, are shown in Map 10. While a number of parts
of the world have languages in which word order changes in polar questions, the
concentration in western and northern Europe is striking. Languages with Philippine-
type voice systems are largely restricted to the Philippines and Taiwan, with the
outlier group in Madagascar reflecting the migration from Southeast Asia ca 1,500
years ago. Languages which have tone as an exponent of verbal agreement are
concentrated in Central America and in Central Africa.




                   Map 10: Features with geographically restricted ranges.
                       Blue = word order changes in polar questions;
                    Red = languages with Philippine-type voice systems;
                     Purple = tone as an exponent of verbal agreement.



Two features listed as widely ubiquitous in Table 19, the existence of a ‘have’ verb in
the language, or the use of a particle to mark polar questions, are shown in Map 11.
Both of these features are found across the map, though with different frequencies in




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different continents. They are so widespread that they have very little probative value
in understanding global morphosyntactic variation.32




                         Map 11: Features with widely ubiquitous distributions.
                                 Blue = language includes a ‘have’ verb;
                         Red = language uses a particle to mark polar questions;
                 Purple = language has both a ‘have’ verb, and a polar question particle.



5. Conclusions


Without explicitly setting out to do so, our study has quantitatively confirmed many
of the insights of 20th-century typological research concerning the main dimensions
of morphosyntactic variation, by finding them as emergent properties of a bottom-up
investigation of a large body of morphosyntactic data. We have shown that much of
the variation between languages, both globally and within macro-areas, can indeed
be largely explained by established typological parameters, as described in 3.1: the
order of subjects and objects with verbs, dependent-marking settings, and the position
of genitives, numerals and adjectives with respect to the nouns that they modify. The
features that correlate with Dimensions 2 and 3, head-marking settings, verbal
elaboration, and a number of features that are reminiscent of ‘Standard Average
European’, have not all been proposed as factors underlying typological variation, but
have been demonstrated here to be as important as more familiar word order

32
     A glance at Map 11 raises the suspicion that these might be relevant features at local levels; the
distribution of ‘have’ verbs in South America, for instance, appears to be concentrated in the north-
west.


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Kalyan & Donohue                                                 Dimensions of Morphosyntactic Variation


universals. The kinds of features described in 3.1 are summarised in Table 20; we can
see that the main correlates of these dimensions are evenly split into those involving
word order, and those involving morphology, with different dimensions addressing
different kinds of word order or morphology. Secondarily we find that the presence
of case-marking morphology, or the lack of extensive morphological processes in the
language, or else word order parameters more relevant to Noun Phrase-internal
elements, are also significant factors in assessing global morphosyntactic variation.


             Dimension        Main type of feature                 Secondary types of features
                  1           Word order (clausal; object)         Dependent marking
                  2           Verbal morphology, head              Isolating profile
                              marking
                  3           Nominal morphology, gender           Ergativity, Clusivity
                  4           Word order (clausal; subject)        Word order (Noun Phrase)


         Table 20: Different features with minimal contribution to global categories of variation.


In Map 12 we see the 3089 languages of the database, coloured according to the
position of each language on Dimensions 1–3, with these dimensions mapped to red,
green and blue colour components, as described in 3.1. Each language is then
represented with a dot of the same colour that was seen in Figure 3, so that in Map
12 the colouring solely represents the position of the individual languages in
typological space as defined by the first three dimensions – that is, the colour scheme
is an emergent property of the linguistic analysis, and in no way involved any
phylogenetic information, and only involved reference to geography in that                     AUTOTYP

areas were used as controls in the analysis.33




33
     This means that Dimension 4 is not represented in the colouring in Map 12. Dimension 4 is shown
in Map 8, and in Appendix 8 alternatives to Map 12, and Figure 3, are shown with colourings
representing different combinations of dimensions, including Dimension 4.


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Linguistic Typology at the Crossroads 3-2 (2023): 132-190




      Map 12: Emergent areality around the world. Map coloured according to the first three
               dimensions of variation, as discussed in 3.1, and shown in Figure 3


A number of regions are clearly identified by both geography and typology, as
discussed in 3.2. Europe (e.g., Haspelmath 2001) is represented with a distinct brown
colour, which is largely due to the languages being moderately low on Dimension 2,
and high on Dimension 3 (compare Figure 3 in Section 3.1 and Figure 4 in Section
3.2.1). The isolating languages of Southeast Asia (e.g., Enfield 2005) are shown in
magenta, as they are relatively high on Dimension 1, low on dimension 2, and
moderately low on Dimension 3 (compare Figure 3 and Figure 6 in 3.2.2). Similar,
though not as extreme, colours are found in the Macro-Sudan Belt (Güldemann 2009)
in west-central Africa, and in Polynesia (e.g., Krupa 1982). Most of Australia (e.g.,
Bowern 2006, Dixon 2017) is in dark blue, as the languages there are low on
Dimension 1 and moderately low on Dimension 2. The only bright green regions, high
on Dimension 2, are found in the Caucasus (Catford 1977) and parts of North America
(e.g., Mithun 1999). In North America the Pacific North-west (Mithun 2010) stands
out, coloured in grey and having much higher values on Dimension 1; a similar
typology is evident in the Oaxaca area in Central America, and the Mamore-Guapore
region of South America (Campbell et al. 1986; Crevels & van der Voort 2008; see
3.2.16). The orange colour found in much of Sub-Saharan Africa represents the Niger-
Congo Bantu languages, high in Dimensions 1, 2 and 3 (and low in Dimension 4,
though this is not apparent from the colouring on the map); see 3.2.10. Separated by
the Macro-Sudan belt, the verb-initial languages of North Africa and Arabia appear in
dark orange, reflecting their position at the top of Dimension 4, but also high on


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Kalyan & Donohue                                                 Dimensions of Morphosyntactic Variation


Dimension 3 (3.2.1). The languages of Taiwan and the Philippines are also high in
Dimension 4, coloured in mauve following their position low on Dimension 3
(3.2.7).34 The densely occupied space low in Dimension 1 and middling in Dimensions
2 and 3 is coloured in dark green, and spans the Eurasian steppe and South Asia
(Janhunen 2023, Emeneau 1956, and many others; see 3.2.3 and 3.2.4); higher on
Dimension 2, but otherwise in a similar position, the languages of the Ethiopian
linguistic areas (Crass 2009) are coloured in a slightly lighter shade of green, and a
darker green is found for the languages of Japan and Korea, representing a position
lower on Dimension 2. Many of the languages of the Andes in South America are
reminiscent of this pan-Eurasian typology (Constenla Umaña 1991, Adelaar 2009,
Michael et al. 2012; see 3.2.15). In addition to these previously-discussed regions in
typological space, we can also identify a number of emergent areas on the map, such
as South-west China, and North-west Australia, Oaxaca (within Meso-America; 3.2.6),
the Kimberleys in Australia, and the South-east Amazon, all clearly identifiable on
Map 12.35
      We mentioned in Section 2 our decision to use nested geographic areas, rather than
genealogies, as controls. While most ‘controls’ in recent linguistics studies are based
on genealogies, we have based our work on culturally-defined areas, specifically a set
of 25 areas slightly modified from the          AUTOTYP    areas, as described in Section 2.
      Our results not only confirm typologists’ intuitions about the features that are most
important for typological classification, but also show the efficacy of a bottom-up
approach to the detection and mapping of areal patterns in morphosyntax.36 The
success (in terms of interpretable results) of the use of a large set of linguistic features,
without any cherry-picking, shows that a holistic (or even ‘super-holistic’) approach
to language typology (following, e.g., Ramat 1986, Plank 1998, Comrie 1988, 2001,
and others) is a valid way to objectively assess claims about linguistic areality or
linguistic universals.

34
     Taken with the grey areas discussed in the Americas, and the mauve from the Philippines, the
languages of North Africa-Arabia represent a third verb-initial linguistic ‘types’, with a large number
of typological features not associated with the verb-initial parameter.
35
     A higher-resolution version of this map can be found in Appendix 7.
36
     It has been suggested that we attempt a similar analysis using the Grambank database. This research
has already been performed (Skirgård et al. 2023), and, owing to the different and smaller set of
languages coded for a different and smaller set of features, the results are very different, though we
note that Skirgård et al. 2023 also appear to have identified word order, head/dependent marking and
gender as relevant to their analysis.


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Linguistic Typology at the Crossroads 3-2 (2023): 132-190


Acknowledgments


We thank two anonymous referees, whose input has greatly improved this paper, and
the input from the editorial team that similarly contributed to the clarity of our
presentation. We are grateful for their feedback.


Abbreviations


 1 = 1st person                     BEN    = benefactive             GEN   = genitive
 2 = 2 person
        nd
                                    Dem = demonstrative              IMPERF   = imperfective
 3 = 3 person
        rd
                                    DIST   = distal                  M   = masculine
 ABS   = absolutive                 ERG    = ergative                PFV   = perfective
 ASP   = aspect                     FUT    = future                  REAL   = realis


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CONTACT
s.kalyan@uq.edu.au
mhdonohue@gmail.com.




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