Innovation of Word Order Harmony
Across Development
Jennifer Culbertson
1
and Elissa L. Newport
2
1School of Philosophy, Psychology, and Language Sciences, Università di Edimburgo
2Department of Neurology, Georgetown University
Keywords:
word order
learning biases,
language acquisition, artificial language learning, regularization,
a n o p e n a c c e s s
j o u r n a l
ABSTRACT
The tendency for languages to use harmonic word order patterns—orders that place heads in
a consistent position with respect to modifiers or other dependents—has been noted since
the 1960s. As with many other statistical typological tendencies, there has been debate
regarding whether harmony reflects properties of human cognition or forces external to it.
Recent research using laboratory language learning has shown that children and adults find
harmonic patterns easier to learn than nonharmonic patterns (Culbertson & Newport, 2015;
Culbertson, Smolensky, & Legendre, 2012). This supports a link between learning and
typological frequency: if harmonic patterns are easier to learn, while nonharmonic patterns
are more likely to be targets of change, Poi, all things equal, harmonic patterns will be more
frequent in the world’s languages. Tuttavia, these previous studies relied on variation in the
input as a mechanism for change in the lab; learners were exposed to variable word order,
allowing them to shift the frequencies of different orders so that harmonic patterns became
more frequent. Here we teach adult and child learners languages that are consistently
nonharmonic, with no variation. While adults perfectly maintain these consistently
nonharmonic patterns, young child learners innovate novel orders, changing nonharmonic
patterns into harmonic ones.
AN APPARENT PREFERENCE FOR HARMONIC WORD ORDER PATTERNS
One of the most well-studied typological tendencies found in language concerns the order-
ing of heads with respect to modifiers and other dependents. Languages tend to use har-
monic orders, placing heads either consistently before or consistently after their dependents
(Dryer, 1992; Greenberg, 1963). A simple example is the noun phrase, where the head noun
can be modified by elements like adjectives and number words. Almost 80% of languages
in the World Atlas of Language Structures Online (Dryer, 2013UN, 2013B) are classified as
placing the noun either before both adjectives and numerals (cioè., N-Adj, N-Num) O
after both of them (cioè., Adj-N, Num-N). The nonharmonic combinations of these two phrase
types are much less common (cioè., N-Adj, Num-N or Adj-N, N-Num). This preference for
harmony is found across many syntactic categories; Per esempio, there is also a strong ten-
dency for languages with head-initial Verb-Object order to have head-initial Preposition-Noun
order and vice versa (see Dryer, 1992). While a number of theoretical proposals have been
made to incorporate a constraint for harmony into grammatical theory (per esempio., Baker, 2001;
Chomsky, 1988; Travis, 1984), the statistical nature of this typological tendency has also led
to alternative explanations. Per esempio, the harmony bias has been argued to reflect general
cognitive or processing constraints (per esempio., favoring shorter dependencies, or simpler grammars;
Citation: Culbertson, J., & Newport,
E. l. (2017). Innovation of Word Order
Harmony Across Development. Open
Mind: Discoveries in Cognitive
Scienza, 1(2), 91–100. https://doi.org/
10.1162/opmi_a_00010
DOI:
https://doi.org/10.1162/opmi_a_00010
Received: 22 Dicembre 2016
Accepted: 17 April 2017
Competing Interests: The authors
declare that they have no competing
interests.
Corresponding Author:
Jennifer Culbertson
jennifer.culbertson@ed.ac.uk
Copyright: © 2017
Istituto di Tecnologia del Massachussetts
Pubblicato sotto Creative Commons
Attribuzione 4.0 Internazionale
(CC BY 4.0) licenza
The MIT Press
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Word Order Harmony Across Development Culbertson, Newport
Culbertson & Kirby, 2016; Hawkins, 1979), or to cognition-external factors like shared in-
heritance among the languages sampled (Dunn, Greenhill, Levinson, & Gray, 2011), or gram-
maticalization (Aristar, 1991; Whitman, 2008). Così, while there is a tendency for harmonic
patterns in a number of syntactic domains, linking this tendency to the human cognitive or
linguistic system requires evidence that
individual language learners or users exhibit a
harmony bias.
The more general issue of understanding how common features of linguistic systems
relate to human cognition is a central question in cognitive science. Recent research suggests
that artificial language learning experiments can provide a way to explore this—both for very
general features of language, like compositionality (per esempio., Kirby, Cornish, & Smith, 2008; Kirby,
Tamariz, Cornish, & Smith, 2015), and for very specific types of rules, like vowel harmony
(per esempio., Finley & Badecker, 2009) or differential case marking (Fedzechkina, Jaeger, & Newport,
2012). Using these methods, laboratory studies have shown that learners prefer harmonic over
nonharmonic word order patterns. Culbertson, Smolensky, and Legendre (2012) trained adult
learners on miniature artificial languages with simple phrases consisting of a noun and an
adjective or a noun and a numeral word. Each language featured a dominant order of each
modifier type, but the opposite order was used in a minority of utterances. In predominantly
harmonic conditions, both the adjective and the numeral tended to appear in the same position
with respect to the noun. Per esempio, learners might hear N-Adj or N-Num in 70% of phrases
and Adj-N or Num-N in the rest. In predominantly nonharmonic conditions, the adjective and
numeral were in different positions with respect to the noun in 70% of phrases. Per esempio,
learners might hear N-Adj or Num-N 70% of the time, Adj-N or N-Num in the rest. When
tested on their production of phrases in the language, learners in harmonic conditions tended to
use the majority pattern they were trained on, while learners in nonharmonic conditions tended
to shift their languages toward a harmonic one. Culbertson and Newport (2015) showed that,
under similar training conditions with variable input languages, child learners 6 A 7 years of
age showed this shift toward harmonic word orders even more strongly.
These studies provide the first direct evidence for a link between cognition and the
frequency of harmonic patterns across the world’s languages: if harmonic patterns are readily
learned and used while nonharmonic patterns are more likely to be targets of change, Poi,
all things equal, harmonic patterns will be more frequent in languages. In other words, IL
tendency for languages to feature harmonic orders is potentially the consequence of a pref-
erence or bias favoring these patterns in individuals, compounded over generations.
Importantly, Tuttavia, these studies have relied on input variation as a mechanism for re-
vealing biases in the lab. Since the languages that learners were trained on allowed all pos-
sible orders, changes to the language could be achieved without innovating new ones.
The preference for harmony was revealed by the unidirectionality of these shifts in the fre-
quency of the varying orders. Tuttavia, while some natural languages allow variation (at
varying levels of systematicity) in the order of nouns with adjectives or numerals, many do
non. In this article we present adult and child learners with artificial languages that are per-
fectly and consistently nonharmonic in word order—that is, that always have their adjectives
in a different position with respect to head nouns than their numerals—and ask whether these
learners will innovate new orders that make nonharmonic languages more harmonic. The re-
sults of this examination will reveal whether the tendency to favor harmony is so strong that
new word order patterns may be developed during learning, E, if so, in which learners this
process is likely to occur.
OPEN MIND: Discoveries in Cognitive Science
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Word Order Harmony Across Development Culbertson, Newport
Tavolo 1. Child lexicon and novel objects; note that modifiers are pseudo-nonce words.
Adjectives
Numerals
LEARNING A CONSISTENT NONHARMONIC LANGUAGE
Participants
Participants were 34 adults and 45 children, all monolingual native English speakers. Adult
participants were undergraduate students at Georgetown University, compensated $10 for
their participation. Child participants were twenty 4- to 5-year-olds (M = 4; 10) and twenty-
five 6- to 7-year-olds (M = 7; 1), recruited from daycares and camps in the Washington, DC,
area.1
Stimuli
Visual and auditory stimuli used for the child participants were identical to those used in
Culbertson and Newport
(2015). Visual stimuli were pictures of four novel objects, shown
in Table 1 along with their nonce-noun labels. Each object could appear modified by one
of three properties (“blue,” “spotted,” “furry”) or three numerosities (“two,” “three,” “four”),
each with a pseudo-nonce label, also shown in Table 1. Stimuli used for the adult partici-
pants were identical to those used in Culbertson et al.
(2012). Visual stimuli were pictures of
ten novel objects (including the four shown in Table 1 below, plus six additional), Quale
could be appear modified by one of five properties (“blue,” “green,” “furry,” “small,” “large”)
or five numerosities (“two” through “six”). All labels used for adults were fully nonce, shown
in Table 2. Auditory stimuli were nonce nouns alone or with a single modifier, produced using
Mac Text-to-Speech (OS 10.6, speaker “Alex,” with pitch augmented using Praat; Boersma,
2001). Stimuli were displayed on a Mac computer using PsychoPy software (Peirce, 2009).
Manipulation
Participants in each age group were randomly assigned to one of two conditions that dif-
fered only in the word order used with each type of modifier. All languages featured phrases
1 Nel 6- to 7-year-old group, 11 additional children were tested but not included in the analysis due to
technical problems (2), failure to complete the training (1), and failure to complete more than two critical trials
for each modifier type (6). Nel 4- to 5-year-old group, 27 additional children were tested but not included in
the analysis due to technical problems (3), failure to complete the training (14), and failure to complete more
than two critical trials for each modifier type (7). Training in this experiment was somewhat lengthy due to the
need for participants to learn to produce the nonce words, and many of the youngest children elected to stop.
The exclusion based on number of trials was motivated by the need for sufficient responses for each modifier
in order to determine a word order preference for each child. This left an average of 43 (SD = 7) E 31
(SD = 15) trials in the 6- A 7- E 4- to 5-year-old groups, rispettivamente. There is no indication of any difference
in results in the partial data for those who did not complete the experiment.
OPEN MIND: Discoveries in Cognitive Science
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Word Order Harmony Across Development Culbertson, Newport
Tavolo 2. Adult lexicon.
Noun labels
Adjectives
Numerals
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comprised of a noun and a single modifier—either an adjective or a numeral. Half of the par-
ticipants were taught a language in which adjectives came after the noun and numerals came
before (“N-Adj, Num-N”); the other half were taught a language with the opposite word orders
(“Adj-N, N-Num”). These are the two nonharmonic languages used in Culbertson et al. (2012)
and Culbertson and Newport (2015). Importantly, Tuttavia, unlike the languages used in those
esperimenti, these languages are completely and consistently nonharmonic; no phrases were
included with the opposite order. We tested only nonharmonic languages in this experiment,
since it is primarily these systems in which participants introduced changes in our previous
studies. These patterns are of particular interest for understanding how learning biases might
induce language change, thereby shaping typology.
Procedure
Each participant was trained and tested in a single session lasting approximately 30 minutes.
Sessions occurred in a quiet room with the participant seated in front of a computer. Nel
case of child participants, the experimenter was seated adjacent; for adults, the experimenter
sat just behind the participant. Each participant was instructed that they would be learning
part of a new language with the help of an “alien informant” named Glermi. The experiment
progressed through a series of training phases, followed by a critical testing phase. In the first
training phase, participants were introduced to the objects and their labels (20 trials total, four
for each noun). Then they saw one of the objects, heard its label, and had to choose the same
object from an array of all four (20 trials). They were then tested on their ability to produce
the novel label corresponding to an object (20 trials). After this, they saw the object modified
by either a property or a numerosity (never both) and heard a phrase describing it (48 trials,
24 noun with adjective, 24 noun with numeral). They completed a final training phase in
which they heard a phrase and had to choose the corresponding picture from an array of four
OPEN MIND: Discoveries in Cognitive Science
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Word Order Harmony Across Development Culbertson, Newport
(UN): Mean proportion of trials on which the correct vocabulary was used by partici-
Figura 1.
pants in each age group; (B): Mean proportion of all trials on which the correct order was used by
participants in each age group. Error bars are bootstrapped 95% confidence intervals.
(48 trials, 24 adjective, 24 numeral). In the critical testing phase, they saw a picture and had
to provide the corresponding phrase (48 trials, 24 adjective, 24 numeral). (For more details
and examples, see Culbertson & Newport, 2015.)
RESULTS
Figure 1A shows mean vocabulary accuracy across trials for participants in each age group
(correct vocabulary for a trial required that both noun and modifier be correct). Figure 1B
shows the extent to which participants matched the input word order pattern they were
exposed to.
The data were analyzed using mixed-effects logistic regression models (using the R pack-
age lme4; Bates, 2010), with all models including at least random intercepts for subject, noun,
and modifier.2 A model predicting use of input order by age group (adult or child), condition,
and their interaction revealed a significant main effect of age [χ2(1) = 29.52, P < .001],
indicating increased input order use for adults compared to children. There was no significant
main effect of condition [χ2(1) = 0.86, p = .35], or interaction between age and condition
[χ2(1) = 0.04, p = .84]. An additional model was run comparing just the two child age
groups, including age, vocabulary accuracy, condition, and their interactions as predictors.
This model revealed no significant main effect of age [χ2(1) = 1.34, p = .24], vocabulary
accuracy [χ2(1) = 2.15, p = .14], or condition [χ2(1) = 5.9, p = .12]. The only significant
interaction was between vocabulary accuracy and age [χ2(1) = 4.57, p = .03]. The latter
indicates that children in the 4- to 5-year-old group were more likely to use the input order
when they also used correct vocabulary.3
2 Random slopes for noun and modifier (i.e., particular adjective or numeral) are included when comparing
among child groups. These are not included when comparing adults and children as the lexicon differed across
them. In the main text we report significance on the basis of likelihood-ratio tests. Main effects in the presence of
interactions were calculated by converting the factor not being tested into a sum-coded numeric representation
and conducting a likelihood-ratio test between models differing only in whether they included a fixed main
effect of the factor of interest (see Levy, 2014, for discussion of this approach).
3 All significant and nonsignificant effects remain so when p values are calculated used the Wald z statis-
tic instead (all factors sum coded): effect of condition on input order use (β = −0.26 ± 0.28, p = .36), effect
of age (adult vs. child) (β = 3.26 ± 0.47, p < .001), effect of age (4–5yrs vs. 6–7yrs) (β = 0.20 ± 0.17, p = .23),
effect of vocabulary accuracy in children (β = −0.10 ± 0.06, p = .11), effect of condition in children (β =
−0.19 ± 0.17, p = .26), and interaction between vocabulary accuracy and age in children (β = −0.13 ± 0.60,
p = .03).
OPEN MIND: Discoveries in Cognitive Science
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Word Order Harmony Across Development Culbertson, Newport
Figure 2. Proportion of learners in each age group who prefer each of the four possible patterns.
These results reveal that, while adults perfectly reproduce the consistent nonharmonic
word order patterns they are trained on, children do not. This means that some proportion
of time, children are using a different order from their input—for example, they may have
consistently heard Adj-N, but produced N-Adj instead. Following Culbertson and Newport
(2015), we calculated each child’s preferred pattern—that is, the pattern they used more than
50% of the time. The four possible patterns include one of the two nonharmonic patterns
participants were trained on or one of the two harmonic patterns not included in the training
materials: prenominal harmonic (“Adj-N, Num-N,” like English) and postnominal harmonic
(“N-Adj, N-Num”). Figure 2 shows the proportion of participants in each age group who
preferentially used each of these patterns, with light green and medium green indicating the
harmonic patterns that were not included in the training input.
The results presented in Figure 2 show that adults are matching the pattern they were
trained on. In contrast, children in the youngest age group tested, 4- to 5-year-olds, showed a
preference for one of the two harmonic patterns almost across the board. The older children
tested, 6- to 7-year-olds, fell between the younger children and adults, with about half prefer-
ring a harmonic pattern and half using the nonharmonic pattern on which they were trained.
The difference between the two child age groups tested was confirmed by a model predict-
ing preferred pattern type (harmonic or nonharmonic) from age [χ2(1) = 4.60, p = .03]. As in
Culbertson and Newport (2015), children show no evidence of preferring the more English-like
prenominal harmonic pattern over the postnominal harmonic pattern that is unlike English.
Our calculation of preferred patterns indicates that a substantial proportion of child par-
ticipants, particularly in the youngest age group, preferred to use a harmonic pattern rather than
match their nonharmonic input. This was not a slight tendency: in almost every case, the result-
ing output languages were used with a high level of consistency. Crucially, even when children
shifted from a nonharmonic to a harmonic pattern, they tended to use that pattern in most or all
of their productions. This is shown in Figure 3. Figure 3A shows how frequently the participants
used the word order that they preferred. (Note that the number of participants included in each
bar varies. For example, almost all young children preferred harmonic patterns, but the few
who did not still used their preferred pattern highly consistently.) Children who used harmonic
patterns were slightly more consistent than those who used the input nonharmonic patterns,
but this difference was not significant [χ2(1) = 2.84, p = .09; see Figure 3A]. Figure 3B illus-
trates the average proportion of the particular preferred pattern used, for those children who
produced a harmonic output pattern. As the figure suggests, this high level of regularity was
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Word Order Harmony Across Development Culbertson, Newport
Figure 3.
(A): Proportion use of preferred pattern for learners in each age group, depending on
whether the preferred pattern was harmonic or not. This illustrates the internal consistency of word
order use, given the word order that they used most frequently. Numbers on each bar indicate the
number of participants included in that bar; (B): Proportion use of each specific preferred pattern
for child learners in each age group, for those who preferred harmonic patterns.
found for children who produced a predominantly prenominal harmonic pattern (i.e., Adj-N
and Num-N) or a predominantly postnominal harmonic pattern (i.e., N-Adj and N-Num). This
was confirmed by a linear regression model [proportion use of prenominal vs. postnominal
harmonic pattern; χ2(1) = 1.68, p = .20]. To summarize, the degree of consistency for indi-
vidual learners was similar whether or not they matched the input patterns they were trained
on, and also whether or not they produced a harmonic pattern like English or unlike English.4
DISCUSSION
The results of this experiment show that when trained on a consistently nonharmonic pattern of
nominal word order—consistently N-Adj, Num-N or consistently Adj-N, N-Num—adults and
children behave differently. Adults perfectly reproduced the nonharmonic pattern they were
trained on, while children typically did not. Importantly, in deviating from their input, children
introduced cross-category word order harmony into the language. When children harmonized
the position of the noun across phrase types, they were equally likely to place the noun last
(like English) or first (unlike English but common in other languages), suggesting that their
behavior does not reflect straightforward transfer from English. Moreover, children used the
harmonic order they innovated very consistently, in accord with Culbertson and Newport
(2015), Hudson Kam and Newport (2005, 2009), and other studies where the input lan-
guages were variable (nondeterministic). Interestingly, the difference between our two child
age groups suggests rapid development toward adult-like matching of nonharmonic patterns
after 5 years of age.
In Culbertson et al.
(2012), where adult learners were trained on variable input, adults
disfavored one of the two nonharmonic patterns: Adj-N, N-Num (replicated in Culbertson,
Smolensky, & Wilson, 2013). This is in fact the most typologically rare of the four patterns,
4 All effects reported as significant remain so if p values are calculated based on Wald z score (all factors sum
coded): effect of age (4–5yrs vs. 6–7yrs) on choice of harmonic pattern (β = −0.75 ± 0.37, p = .03); effect of
pattern type (harmonic vs. non-harmonic) on proportion use of preferred pattern (β = −0.06 ± 0.03, p = .10);
effect of harmonic pattern (pre- or postnominal) on proportion use of preferred pattern (β = −0.04 ± 0.03,
p = .21).
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Word Order Harmony Across Development Culbertson, Newport
suggesting the possibility of an additional bias targeting this particular nonharmonic pattern.
However, as in Culbertson and Newport (2015), here we do not find any differences between
the two nonharmonic conditions, either for children or for adults. In the case of adults, it seems
likely that this is due to the role of variation in allowing learners to exert subtle shifts to the
input without introducing new variants. By contrast, young children more readily introduce
language changes, exhibiting such a strong harmony bias that differences between the nonhar-
monic patterns become less clear. It remains to be seen if developmental changes in knowledge
of adjective or numeral syntax impact the emergence of a bias against Adj-N, N-Num when
variation is present (see Culbertson & Newport, 2015, and also Goldberg, 2013).
In order to make a nonharmonic input language become harmonic, children in our
experiment must innovate or, perhaps more accurately, generalize the ordering pattern from
one phrase type to another. There are a number of possible mechanisms that may be respon-
sible for this kind of generalization. First, in previous work we have suggested that learners
are more likely to infer harmonic grammars compared to nonharmonic ones because the for-
mer are representationally simpler (Culbertson & Kirby, 2016; Culbertson & Newport, 2015).
Briefly, harmonic grammars require only a single rule governing the order of nouns and mod-
ifiers, while nonharmonic grammars require additional specific rules for each modifier type.
A related possibility is that, for very young learners, adjectives and numerals may not yet be
distinct categories in the grammar. The latter would suggest a drive to generalize a single
word order rule across lexical items rather than across categories. This may be particularly
strong in children whose native language uses the same order for both of these modifier types.
An important next step is therefore to investigate harmonizing behavior in children whose
native language provides more robust evidence for syntactically distinguishing adjectives from
numerals (Braquet & Culbertson, in press).
Taken together with previous studies, the results reported here provide evidence sup-
porting a link between human learning and one of the most well-known typological universals
of syntax. Harmonic languages are easier for both adults and children to learn, while nonhar-
monic patterns are more likely to be changed by learners. Children in particular dramatically
shift nonharmonic patterns to harmonic ones. How do these laboratory investigations of the
early stages of word order learning relate to natural language acquisition? Of course, children
learning a nonharmonic language in a natural setting do not radically change the language
they are exposed to when they produce simple phrases like a noun and an adjective. How-
ever, children presumably receive much more evidence about the syntax of the language they
are acquiring before they begin producing phrases like these. Here we are requiring learners
to produce phrases when they have relatively little evidence to go on, allowing us to see prior
expectations or biases that we might not see in a natural language setting. Indeed, in our study,
young children who were more successful at learning the lexicon of the language were less
likely to shift the input word order. What our results suggest is that, even if we don’t see produc-
tion errors in natural language acquisition indicating a preference for harmonic patterns—for
example, in children acquiring nonharmonic languages—a strong bias may nevertheless be
present. This bias continues into adulthood, but less strongly.
While the cognitive biases that shape linguistic systems may be relatively strong in initial
stages of learning, weak biases that persist in development can still exert pressure for language
change over generations (Kirby et al., 2008; Thompson, Kirby, & Smith, 2016). The extent to
which these pressures in natural languages come from child learners or adults remains less clear
and may be specific to the phenomenon in question. For example, nonharmonic languages
may be more susceptible to change through influence from language contact, sociolinguistic
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variation, or the introduction of second language learners to the population (Labov, 1994;
Trudgill, 2001). These are all sources of variation, which may trigger observable effects from
the weak biases of adult language users. Alternatively, word order change may be driven by
small deviations from the input due to reanalysis in language acquisition by children. Further
research is needed to better understand the potential role of these precise mechanisms in
linking the harmony bias to language typology.
ACKNOWLEDGMENTS
Thanks to Sarah Furlong and to participants and their parents. This research was partially
supported by NIH Grants HD37082 and DC014558 and by funds from the Center for Brain
Plasticity and Recovery, Georgetown University.
AUTHOR CONTRIBUTIONS
JC and ELN designed the research, ELN supervised data collection, JC analyzed data, JC and
ELN wrote the article.
REFERENCES
Aristar, A. R. (1991). On diachronic sources and synchronic pattern:
An investigation into the origin of linguistic universals. Language,
67, 1–33.
Baker, M. (2001). The atoms of language: The mind’s hidden rules
of grammar. New York, NY: Basic Books.
Bates, D.
(2010). lme4: Mixed-effects modeling with R. Retrieved
from http://lme4.r-forge.r-project.org/book
Boersma, P. (2001). Praat, a system for doing phonetics by computer.
Glot International, 5, 341–345.
Braquet, G., & Culbertson, J. (in press). Harmony in a non-harmonic
language: Word order learning in French children. Proceedings
of the 39th Annual Meeting of the Cognitive Science Society.
Chomsky, N.
(1988). Language and problems of knowledge: The
Managua lectures. Cambridge, MA: MIT Press.
Culbertson, J., & Kirby, S.
(2016). Simplicity and specificity in
language: Domain general biases have domain specific effects.
Frontiers in Psychology, 6.
Culbertson, J., & Newport, E. L. (2015). Harmonic biases in child
In support of language universals. Cognition, 139,
learners:
71–82.
Culbertson, J., Smolensky, P., & Legendre, G.
(2012). Learning
biases predict a word order universal. Cognition, 122, 306–329.
(2013). Cognitive
linguistic universals, and constraint-based grammar
biases,
learning. Topics in Cognitive Science, 5, 392–424.
Culbertson, J., Smolensky, P., & Wilson, C.
Dryer, M. (1992). The Greenbergian word order correlations. Lan-
guage, 68, 81–183.
Dryer, M. (2013a). Order of adjective and noun. In M. S. Dryer &
M. Haspelmath (Eds.), The world atlas of language structures
online. Leipzig: Max Planck Institute for Evolutionary Anthro-
pology. http://wals.info/chapter/87
Dryer, M. (2013b). Order of numeral and noun. In M. S. Dryer &
M. Haspelmath (Eds.), The world atlas of language structures
online. Leipzig: Max Planck Institute for Evolutionary Anthro-
pology. http://wals.info/chapter/89
Dunn, M., Greenhill, S., Levinson, S., & Gray, R. (2011). Evolved
structure of language shows lineage-specific trends in word-
order universals. Nature, 473, 79–82.
Fedzechkina, M., Jaeger, T. F., & Newport, E. L.
(2012). Lan-
guage learners restructure their
to facilitate efficient
communication. Proceedings of the National Academy of Sci-
ences, 109, 17897–17902.
input
Finley, S., & Badecker, W. (2009). Artificial language learning and
feature-based generalization. Journal of Memory and Language,
61, 423–437.
Goldberg, A. E.
(2013). Substantive learning bias or an effect of
familiarity? Comment on Culbertson, Smolensky, and Legendre
(2012). Cognition, 127, 420–426.
Greenberg, J. (1963). Some universals of grammar with particular
In J. Greenberg
reference to the order of meaningful elements.
(Ed.), Universals of language (pp. 73–113). Cambridge, MA: MIT
Press.
Hawkins, J. A.
(1979).
Implicational universals as predictors of
word order change. Language, 55, 618–648.
Hudson Kam, C., & Newport, E. (2005). Regularizing unpredictable
variation. Language Learning and Development, 1, 151–195.
Hudson Kam, C., & Newport, E. (2009). Getting it right by getting it
wrong: When learners change languages. Cognitive Psychology,
59, 30–66.
Kirby, S., Cornish, H., & Smith, K.
(2008). Cumulative cultural
evolution in the laboratory: An experimental approach to the
Proceedings of the
origins of structure in human language.
National Academy of Sciences, 105, 10681–10686.
Kirby, S., Tamariz, M., Cornish, H., & Smith, K. (2015). Compres-
sion and communication in the cultural evolution of linguistic
structure. Cognition, 141, 87–102.
OPEN MIND: Discoveries in Cognitive Science
99
l
D
o
w
n
o
a
d
e
d
f
r
o
m
h
t
t
p
:
/
/
d
i
r
e
c
t
.
m
i
t
.
/
e
d
u
o
p
m
i
/
l
a
r
t
i
c
e
-
p
d
f
/
/
/
/
/
1
2
9
1
1
8
6
8
2
3
3
o
p
m
_
a
_
0
0
0
1
0
p
d
.
i
f
b
y
g
u
e
s
t
t
o
n
0
7
S
e
p
e
m
b
e
r
2
0
2
3
Word Order Harmony Across Development Culbertson, Newport
Labov, W.
(1994). Principles of language change, Vol. 1: Internal
Travis, L.
(1984). Parameters and effects of word order variation.
factors. New York, NY: Blackwell.
Levy, R.
(2014). Using R formulae to test for main effects in the
presence of higher-order interactions. arXiv. Retrieved from
https://arxiv.org/abs/1405.2094v1
Peirce, J. W.
(2009). Generating stimuli for neuroscience using
PsychoPy. Frontiers in Neuroinformatics, 2.
Thompson, B., Kirby, S., & Smith, K.
(2016). Culture shapes the
evolution of cognition. Proceedings of the National Academy of
Sciences, 113, 4530–4535.
(Unpublished doctoral dissertation). MIT, Cambridge, MA.
Trudgill, P. (2001). Contact and simplification: Historical baggage
and directionality in linguistic change. Linguistic Typology, 5,
371–374.
Whitman, J.
(2008). The classification of constituent order gen-
In J. Good (Ed.), Lin-
eralizations and diachronic explanation.
guistic universals and language change (pp. 233–252). Oxford,
England: Oxford University Press.
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D
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t
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s
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e
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e
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