Proceedings of the Second Workshop on Psychocomputational Models of Human Language Acquisition, pages 53–68,
Ann Arbor, June 2005. c©2005 Association for Computational Linguistics
Item-based Constructions and the Logical Problem 
 
Brian MacWhiney 
Department of Psychology 
Carnegie Mellon University 
Pitsburgh, PA 15213 
macw@cmu.edu 
 
 
 
 
 
Abstract 
The logical problem of language is 
grounded on arguents from poverty 
of positive evidence and arguments 
from poverty of negative evidence. 
Careful analysis of child language cor-
pora shows that, if one assumes that 
children learn through item-based con-
structions, there is an abundance of 
positive evidence. Arguments regarding 
the poverty of negative evidence can 
also be adressed by the mechanism of 
conservative item-based learning. When 
conservativism is abandoned, children 
can rely on competition, cue construc-
tion, monitoring and probabilistic iden-
tification to derive information from 
positive data to recover fro overgener-
alization. 
1. The Logical Problem 
Chomsky (1957, 1980) has argued that the child’s 
acquisition of grammar is ‘hopelessly underdeter-
mined by the fragmentary evidence available.’ He 
attributed this indeterminacy to two major sources. 
The first is the degenerate nature of the input. Ac-
cording to Chomsky, the sentences heard by the 
child are so ful of retracing, error, and incomple-
tion that they provide no clear indication of the 
posible sentences of the language. Coupled with 
this problem of input degeneracy is the problem of 
unavailability of negative evidence. According to 
this view, children have a hard time knowing 
which forms of their language are acceptable and 
which are unacceptable, because parents fail to 
provide consistent evidence regarding the un-
grammaticality of unacceptable sentences. Worse 
stil, when such evidence is provided, children ap-
pear to ignore it. 
Chomsky’s (1957) views about the degeneracy 
of the input did not stand up well to the test of 
time. As Newport, Gleitman & Gleitman (197) 
reported, ‘the speech of mothers to children is 
unswervingly well-formed.’ More recently, Sagae, 
Lavie & MacWhiney (204) examined several of 
the corpora in the CHILDES database and found 
that adult input to children can be parsed with an 
accuracy level parallel to that for corpora such as 
the Wall Street Journal database. 
This evidence for well formedness of the input 
did not lead to the colapse of the ‘argument from 
poverty of stimulus’ (APS). However, it did place 
increased weight on the remaining claims regard-
ing the absence of relevant evidence. The overall 
claim is that, given the absence of appropriate 
positive and negative evidence, no child can ac-
quire language without guidance from a rich set of 
species-specific inate hypotheses. Some refer to 
the argument from poverty of stimulus as the ‘logi-
cal problem of language acquisition (Baker, 1979), 
while others have called it ‘Plato’s Problem,’ 
‘Chomsky’s Problem,’ ‘Gold’s Problem,’ or 
‘Baker’s Paradox.’ 
2. Absence of Negative Evidence 
In the 1970s, generativist analyses of learnability 
(Wexler & Hamburger, 1973) relied primarily on 
an analysis presented by Gold (1967). Gold’s 
analysis contrasted two different language-learning 
situations: text presentation and informant presen-
tation. With informant presentation, the language 
learner can receive feedback from an infallible in-
formant regarding the grammaticality of every 
candidate sentence. This corrective feedback is 
called ‘negative evidence’ and it only requires that 
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ungrammatical strings be clearly identified as un-
acceptable. Whenever the learner formulates an 
overly general guess about some particular linguis-
tic structure, the informant wil label the resulting 
structure as ungrammatical and the learner wil use 
this information to restrict the developing gram-
mar. Based on initial empirical results reported by 
Brown & Hanlon (1970), Gold argued that nega-
tive evidence is not available to the child and that 
language learning cannot be based on informant 
presentation. 
Marcus (193) has argued that the feedback that 
parents provide does not discriminate consistently 
between grammatical and ungrammatical construc-
tions. As a result, children cannot rely on simple, 
overt negative evidence for recovery from over-
generalization. Although I wil argue that parents 
provide positive evidence in a form that solves the 
logical problem (Bohannon et al., 190), I agree 
with the observation that this evidence does not 
constitute overt grammatical corection of the type 
envisioned by Gold. 
3. Absence of Positive Evidence 
Begining about 1980, generative analyses of 
learnability began to shift away from an emphasis 
on the unavailability of negative evidence to argu-
ments based on the unavailability of positive evi-
dence.  This conceptual shift led to a relative 
decline in attention to recovery from overgenerali-
zation and an increase in atention to reported cases 
of error-free learning. For example, Chomsky’s 
(1980) statement of the logical problem relies on 
the notion of error-free learning without positive 
evidence.  The argumentation here is that, if a 
structure is never encountered in the input, correct 
use of this structure would have to indicate inate 
knowledge. 
Researchers have claimed that the child pro-
duces error-free learning without receiving positive 
evidence for structures such as: structural depend-
ency, c-command, the binding conditions, subja-
cency, negative polarity items, that-trace deletion, 
nominal compound formation, control, auxiliary 
phrase ordering, and the empty category principle. 
In each of these cases, it is necessary to assume 
that the underlying universal is a part of the non-
parameterized core of universal grammar.  If the 
dimension involved were parameterized, there 
would be a need for some form of very early pa-
rameter seting (Wexler, 198), which could itself 
introduce some error. Thus, we would expect er-
ror-free learning to occur primarily for those as-
pects of the grammar that are completely universal 
and not parameterized. Parameterized features, 
such as subject pro-drop, could stil be guided by 
universal gramar. However, their learning would 
not necesarily be error-free. 
3.1. Structural dependency 
The paradigm case of error-free learning is the 
child’s obedience to the Structural Dependency 
condition, as outlined by Chomsky in his formal 
discusion with Jean Piaget (Piattelli-Palmarini, 
1980). Chomsky notes that children learn early on 
to move the auxiliary to initial position in ques-
tions, such as ‘Is the man coming?’ One formula-
tion of this rule is that it stipulates the movement 
of the first auxiliary to initial position. This formu-
lation would be based on surface order, rather than 
structural relations. However, if children want to 
question the proposition given in (1), they wil 
never produce a movement such as (2). Instead, 
they wil always produce (3). 
1. The man who is runing is coming. 
2. Is the man who _ runing is coming? 
3. Is the man who is runing _ coming?’ 
In order to produce (3), children must be basing the 
movement on structure, rather than surface order. 
Thus, according to Chomsky, they must be in-
nately guided to formulate rules in terms of struc-
ture. 
In the theory of barriers (Chomsky, 1986),  the 
repositioning of the auxiliary in the tree and then in 
surface structure involves a movement of INFL to 
COMP that is subject to the head movement con-
straint. In (2) the auxiliary would need to move 
around the N’ of ‘man’ and the CP and COMP of 
the relative clause, but this movement would be 
blocked by the head movement constraint (HMC). 
No such barriers exist in the main clause. In addi-
tion, if the auxiliary moves as in (2), it leaves a gap 
that wil violate the empty category principle 
(ECP). Chomsky’s discusion with Piaget does not 
rely on these details. Chomsky simply argues that 
the child has to realize that phrasal structure is 
somehow involved in this process and that one 
cannot formulate the rule of auxiliary movement as 
‘move the first auxiliary to the front.’  
54
Chomsky claims that, ‘A person might go 
through much or all of his life without ever having 
been exposed to relevant evidence, but he wil 
nevertheless unerringly employ the structure-
dependent generalization, on the first relevant oc-
casion.’ A more general statement of this type pro-
vided by Hornstein & Lightfoot (1981) who claim 
that, ‘People attain knowledge of the structure of 
their language for which no evidence is available 
in the data to which they are exposed as children.’  
In order to evaluate these claims empirically, we 
need to know when children first produce such 
sentences and whether they have been exposed to 
relevant examples in the input prior to this time. In 
searching for instances of relevant input as well as 
first uses, we should include two types of sen-
tences. First, we want to include sentences such as 
(3) in which the moved verb was a copula in the 
relative clause, as well as sentences with auxilia-
ries in both positions, such as ‘Wil the boy who is 
wearing a Yankee’s cap step forward?’ The auxil-
iaries do not have to be lexically identical, since 
Chomsky’s argument from poverty of stimulus 
would also apply to a child who was learning the 
movement rule on the basis of lexical class, as op-
posed to surface lexical form. 
Examining the TreeBank structures for the Wall 
Street Journal in the Penn TreeBank, Pulum & 
Scholz (Pulum & Scholz, 202) estimate that adult 
corpora contain up to 1% of such sentences. How-
ever, the presence of such structures in formal 
writen English says litle about their presence in 
the input to the language-learning child. A search 
by Lewis & Elman (201) of the input to English-
speaking children in the CHILDES database 
(MacWhiney, 200) turned up only one case of 
this structure out of approximately 3 milion uter-
ances. Since CHILDES includes god sampling of 
target children up to age 5;0, we can safely say that 
positive evidence for this particular structure is 
seldom encountered in the language addressed to 
children younger than 5;0. 
Because children do not produce sentences of 
this type themselves, it is difficult to use produc-
tion data to demonstrate the presence of the con-
straint. Crain & Nakayama (1987) attempted to get 
around this problem by eliciting these forms from 
children directly.  They asked children (3;2 to 
5;1) to, ‘Ask Jabba if the boy who is watching 
Mickey is happy.’ Children responded with a vari-
ety of structures, none of which involved the 
movement of the auxiliary from the relative clause. 
Unfortunately, this elicitation procedure encour-
ages children to treat the relative clause (‘the boy 
who is watching Mickey’) as an imitated chunk. 
Despite the serious methodological limitation in 
this particular study, it seems reasonable to believe 
that four-year-old children are begining to behave 
in accordance with the Structural Dependency 
condition for sentences like (2) and (3). But does 
this mean that they reach this point without learn-
ing? 
There is another type of sentence that provides 
equally useful positive evidence regarding auxil-
iary movement.  These are wh-questions with em-
bedded relative clauses. It turns out that there are 
hundreds of input sentences of this type in the 
CHILDES corpus. Most of these have the form of 
(4), but some take the form of (5). 
4. Where is the dog that you like? 
5. hich is the dog that is clawing at the 
dor? 
In (5) the child receives clear information demon-
strating that moved auxiliaries derive from the 
main clause and not the relative clause. Using evi-
dence of the type provided in (4), the child simply 
learns that moved auxiliaries and the wh-words 
that accompany them are arguments of the verb of 
the main clause.  Sentences like (4) and (5) are 
highly frequent in the input to children and both 
types instruct the child in the same correct gener-
alization. 
Based on evidence from the main clause, the 
child could formulate the rule as a placement after 
the wh-word of the auxiliary that is conceptually 
related to the verb being questioned. In other 
words, it is an attachment to the wh-word of an 
argument of the main verb. This is a complex ap-
plication of the process of item-based construction 
generation proposed in MacWhiney (1975, 1982). 
This formulation does not rely on barriers, ECP, 
HCP, INFL, COMP, or movement. It does rely on 
the notion of argument structure, but only as it 
emerges from the application of item-based con-
structions. Given this formulation, a few simple 
yes–no questions would be enough to demonstrate 
the patern.  When children hear ‘is the baby 
happy’ they can learn that the initial copula auxil-
iary ‘is’ takes a subject argument in the next slot 
and a predicate argument in the folowing slot. 
They wil learn similar frames for each of the other 
fronted auxiliaries. When they then encounter sen-
55
tences such as (11) and (12), they wil further 
elaborate the item-based auxiliary frames to allow 
for positioning of the initial wh-words and for at-
tachment of the auxiliaries to these wh-words. 
One might argue that this learning scenario 
amounts to a restatement of Chomsky’s claim, 
since it requires the child to pay attention to rela-
tional patterns, rather than serial order as calcu-
lated from the begining of the sentence. However, 
if the substance of Chomsky’s claim is that chil-
dren learn to fil argument slots with compound 
constituents, then his analysis seems indistinguish-
able from that of MacWhiney (1975; 1987a). 
3.2  Auxiliary phrases 
Kimball (1973) presented perhaps the first example 
of a learnability problem based on poverty of posi-
tive evidence. He noted that children are exposed 
to scores of sentences with zero, one, or two auxil-
iaries as in (6)–(13). However, his searches of a 
milion sentences in early machine-readable cor-
pora located not a single instance of a structure 
such as (13). 
6. It rains. 
7. It may rain. 
8. It may have rained. 
9. It may be raining. 
10. It has rained. 
1. It has been raining. 
12. It is raining. 
13. It may have been raining. 
Kimball argued that, despite the absence of posi-
tive data for (13), children are stil able to infer its 
grammaticality from the data in (6) to (12). He 
tok this as evidence that children have inate 
knowledge of structural compositionality. The em-
pirical problem with Kimball’s analysis is that sen-
tences like (13) are not nearly as rare as his corpus 
analysis sugests.  My search of the CHILDES 
database for the string ‘might have been’ located 
27 instances in roughly 3 milion sentences. In ad-
dition there were 24 cases of ‘could have been’, 15 
cases of ‘should have been’, and 70 cases of 
‘would have been.’ Thus, there seems to be litle 
shortage of positive evidence for the direct learn-
ing of this pattern. Perhaps Kimball’s findings to 
the contrary arose from focusing exclusively on 
‘may’, since a search for ‘may have been’ turned 
up only 5 cases. 
3.3 The complex-NP constraint 
The complex-NP constraint blocks movement of a 
noun from a relative clause, as in (14) and (15). 
14. *Who did John believe the man that kised 
_ arrived 
15. Who did John believe _ kised his budy? 
This same constraint also blocks movement 
from prepositional phrases and other complex NPs, 
as in (16) – (18): 
16. *Who did pictures of __ surprise you? 
17. *hat did you see a happy __ ? 
18. *What did you stand between the wall and 
__ ? 
The constraint in (18) has also been treated as 
the coordinated-NP constraint in some accounts. 
Although it appears that most children obey these 
constraints, there are some exceptions. Wilson & 
Peters (198) list these violations of the complex 
NP constraint from Wilson’s son Seth between the 
ages of 3;0 and 5;0. 
19. What am I cooking on a hot _ ? (stove) 
20. hat are we gona lok for some _ ? 
(houses) 
21. What is this a funy _ , Dad? 
2. hat are we gona push number _ ? (9) 
23. Where did you pin this on my _ ? (robe) 
24. hat are you shaking all the _ ? (bater 
and milk) 
25. What is this medicine for my _ ? (cold) 
These seven violations all involve separation of a 
noun from its modifiers. Two other examples, il-
lustrate violation of the complex-NP constraint in 
other environments: 
26. What did I get lost at the _ , Dad? 
27. hat are we gona go at Auntie and _ ?  
Here, the prohibited raising involves prepositional 
phrases and a conjoined noun phrase. Violations of 
the latter type are particularly rare, but stil do oc-
cur ocasionally. 
One might object that a theory of universal 
grammar should not be rejected on the basis of a 
few violations from a single child. However, other 
observers have reported similar errors. In the 
recordings from my sons Ros and Mark, I 
observed a few such violations. One occurred 
when my son Mark (at 5;4.4) said, ‘Dad, next time 
when it's Indian Guides and my birthday, what do 
you think a picture of __ should be on my cake?’ 
Catherine Snow reports that at age 10;10, her son 
Nathaniel said, ‘I have a fever, but I don't want to 
56
said, ‘I have a fever, but I don't want to be taken a 
temperature of.’ 
Most researchers would agree that violations of 
the complex-NP constraint are rare, but certainly 
not nonexistent. At the same time, the structures or 
meanings that might triger these violations are 
also very rare, as is the input that would tell the 
child how to handle these structures. Given this, it 
seems to me that these patterns cannot reasonably 
be described as cases of error-free learning.  In-
stead, we should treat them as instances of ‘low-
error constructions.’ In this regard, they resemble 
errors such as stative progressives (‘I am know-
ing’) and double-object violations (‘He recom-
mended the library the bok’). As son as we shift 
from error-free learning to low-error learning, we 
need to apply a very different form of analysis, 
since we now have to explain how children recover 
from making these overgeneralization errors, once 
they have produced them. This then induces us to 
again focus on the availability of negative evi-
dence. 
Of course, we could assume that the violation of 
the complex-NP constraint was a transient per-
formance error and that, once the relevant per-
formance factors are eliminated, the constraints of 
UG operate to block further wh-raising from com-
plex noun phrases. But the important point here is 
that we now need to consider specific mechanisms 
for allowing for recovery from overgeneralization, 
even for what have been offered as the clearest 
cases of the application of universal constraints. 
3.4  Binding conditions 
Binding theory (Chomsky, 1981) offers three pro-
posed universal conditions on the binding of pro-
nouns and reflexives to referents. Sentence (28) 
ilustrates two of the constraints. In (28), ‘he’ can-
not be coreferential with ‘Bil’ because ‘Bil’ does 
not c-command the pronoun. At the same time, 
‘himself’ must be coreferential with ‘Bil’ because 
it is a clausemate and does c-command ‘Bil.’ 
28. He said that Bil hurt himself. 
When attempting to relate the logical problem to 
the study of the binding constraints, it is important 
to remember that the sentences produced or inter-
preted are fuly grammatical. However, the inter-
pretation in which the pronoun is coreferential with 
the ful NP is disallowed by the binding principles. 
This means that, to study the imposition of the 
constraints, researchers must rely on comprehen-
sion studies, often with very young children. 
It is well known that children often fail to aply 
these principles, even in carefuly controled ex-
periments (O'Grady, 197). Various accounts have 
been offered to reconcile these facts with the sup-
posed universality of the constraint. However, one 
posibility that has seldom been explored is the 
idea that the binding conditions are learned on the 
basis of positive data. To ilustrate the role that 
learning can play in this area, consider a study of 
long-distance movement of adjuncts by De 
Viliers, Roeper & Vainika (De Viliers et al., 
190). Children were divided into two age groups: 
3;7 to 5;0 and 5;1 to 6;1. They were given sen-
tences such as: 
29. When did the boy say he hurt himself? 
30. hen did the boy say how he hurt him-
self? 
31. Who did the boy ask what to throw? 
For (29), 4% of the children gave long distance 
interpretations, associating ‘when’ with ‘hurt him-
self’, rather than ‘say.’ For (30), with a medial wh-
phrase blocking a long-distance interpretation, only 
6% gave long-distance responses. This shows that 
children were sensitive to the conditions on traces, 
in accord with P&P (Chomsky & Lasnik, 193) 
theory. However, the fact that sensitivity to this 
contrast increases markedly acros the two age 
groups indicates that children are learning this pat-
tern. In the youngest group, children had trouble 
even understanding sentences with medial argu-
ments like (31). The fact that this ability improves 
over time again points to learning of the posible 
interpretations of these structures. 
Children can learn to interpret these sentences 
correctly by applying conservative learning princi-
ples that rely on positive data.  First, they learn 
short-distance interpretations that attach the wh-
word to the main clause.  Then, when they hear 
sentences with medial “how” they add the addi-
tional posibility of the long-distance interpreta-
tion. However, they do this in a conservative item-
based manner, limiting the new interpretation to 
sentences like (30) with medial “how.” 
P&P theory can also provide an account of this 
development in terms of the setting of parameters. 
First, children must realize that their language al-
lows movement, unlike Chinese. Next they must 
decide whether the movement can be local, as in 
German, or both local and distant as in English. 
57
Finally, they must decide whether the movement is 
indexed by pronouns, traces, or both. However, 
once a parameter-setting account is detailed in a 
way that requires careful attention to complex cue 
patterns over time (Butery, 204; Sakas & Fodor, 
201), it can be difficult to distinguish it from a 
learning account. Using positive evidence, children 
can first learn that some movement can occur. 
Next, they can learn to move locally and finally 
they can acquire the cues to linking the moved ar-
gument to its original argument position, one by 
one. 
3.5  Learnability or learning? 
What have we learned from our examination of 
these four examples? First, we have seen that the 
application of universal constraints is not error-
free. This is particularly true in the case of the 
binding conditions. Because the binding conditions 
involve parameter setting, it is perhaps not surpris-
ing that we see errors in this domain. However, we 
also find errors in the application of the non-
parameterized constraint against raising from com-
plex noun phrases. Only in the case of the struc-
tural dependency condition do we find no errors. 
However, for that structure there is also no usage at 
all by either parents or children, unless we consider 
attachment of auxiliaries to wh-words, which is 
quite frequent. It is posible that error-free learning 
exists in various other corners of syntactic, seman-
tic, or lexical learning. But there is no evidence 
that error-free learning occurs in association with 
an absence of positive evidence. This is the crucial 
association that has been claimed in the literature 
and it is the one that we have shown to be false. 
Second, for each of the four learnability prob-
lems we examined, we have seen that there are 
effective learning methods based on available posi-
tive evidence. This learning involves mechanisms 
of conservative, item-based learning folowed by 
later generalization.  
4. Multiple Solutions 
Having now briefly surveyed the role of the logical 
problem in generative theory, we turn next to a 
consideration of seven factors that, operating to-
gether, allow the child to solve the logical problem. 
Of these seven factors, the first two are simply 
formal considerations that help us understand the 
scope of the problem.  The last five are processes 
that can actually guide the child during acquisition. 
4.1  Limiting the class of grammars 
The first solution to the logical problem adresses 
the Gold analysis directly by showing how lan-
guage can be generated from finite-state gramars 
(Reich, 1969). For example, Hauser (199) has 
developed an efficient parser for left-associative 
grammars. He has shown that left-associative 
grammar can be expressed as a finite automaton 
that orders words in terms of part-of-speech cate-
gories. Because we know that finite automata can 
be identified from positive evidence (Hopcroft & 
Ulman, 1979), this means that children should be 
able to learn left-associative gramars directly 
without trigering a logical problem. Given the 
fact that these grammars can parse sentences in a 
time-linear and psycholinguistically plausible fash-
ion, they would seem to be excellent candidates for 
further exploration by child language researchers. 
A formal solution to the logical problem also 
arises in the context of the theory of categorical 
grammar. Kanazawa (198) shows that a particular 
class of categorial grammars known as the k-
valued grammars can be learned on positive data. 
Moreover, he shows that most of the customary 
versions of categorial grammar discused in the 
linguistic literature can be included in this k-valued 
class. Shinohara (194) and Jain, Osherson, Royer 
& Sharma (199) examine stil further classes of 
complex non-finite languages that can be learned 
on the basis of positive data alone. These attempts 
to recharacterize the nature of human language by 
revised formal analysis all stand as useful ap-
proaches to the logical problem. By characterizing 
the target language in a way that makes it learnable 
by children, linguists help bridge the gap between 
linguistic theory and child language studies. 
4.2  Revised end-state criterion 
The second solution to the logical problem in-
volves resetting our notion of what it means to ac-
quire an end-state grammar. Horning (1969) 
showed that, if the language identification is al-
lowed to involve a stochastic probability of identi-
fication, rather than an absolute guarantee of no 
further error ever, then language can be identified 
on positive evidence alone. It is surprising that this 
58
solution has not received more attention, since this 
analysis undercuts the core logic of the logical 
problem, as it applies to the learning of all rule sys-
tems up to the level of context-sensitive grammars. 
If learning were deterministic, children would go 
through a series of attempts to hypothesize the 
‘correct’ grammar for the language. Once they hit 
on the correct identification, they would then never 
abandon this end-state grammar. The fact that 
adults make speech errors and differ in their judg-
ments regarding at least some syntactic structures 
sugests that this criterion is to strong and that the 
view of grammar as stochastic is more realistic. 
4.3  Conservative Item-based Learning 
The third solution to the logical problem empha-
sizes the conservative nature of children’s lan-
guage learning.  The most direct way for a 
language learner to solve Gold’s problem is to 
avoid formulating overly general grammars in the 
first place. If the child never overgeneralizes, there 
is no problem of recovery from overgeneralization 
and no need for negative evidence or corrective 
feedback. Taking this basic idea one step further, 
let us imagine that grammars are ordered strictly in 
terms of their relative generative power. If this is 
true, then the forms generated by a grammar are a 
subset of the next slightly larger grammar. This is 
known as the Subset Principle. If the child always 
choses the least powerful grammar that is consis-
tent with the input data, then the problem of the 
unavailability of negative evidence disappears and 
learning can be based simply on positive evidence. 
The Subset Principle has often been used to ar-
gue for abstract relations between grammars. For 
example, Fodor & Crain (1987) argue that the 
child learns the periphrastic dative (‘give the bok 
to John’) for each new verb and only asumes that 
the double object construction (‘give John the 
bok’) can be applied if it is atested in the input. 
In this particular case, the grammar with only the 
periphrastic is ordered as a subset of the grammar 
with both constructions. This folows from the 
principles for expansion of curly braces in GPSG.  
Conservatism can control acquisition of these 
structures without invoking the Subset Principle. 
The theory of item-based acquisition 
(MacWhiney, 1975, 1982, 1987a; Tomasello, 
200) holds that syntactic learning is driven by the 
induction and combination of item-based construc-
tions. Each item-based construction specifies a set 
of slots for arguments. Initially, these slots encode 
features that are specific to the first words encoun-
tered in this slot during comprehension.  For ex-
ample, the item ‘more’ has a slot for a folowing 
argument. If the first combinations the child picks 
up from comprehension are ‘more cookies’ and 
‘more milk’, then this slot wil initially be limited 
to foods. However, as the child hears ‘more’ used 
in additional combinations, the semantics of the 
slot filer wil extend to any mass noun or plural. 
This learning is based entirely on generalization 
from positive evidence. 
When learning the item-based construction for 
‘give’, children encounter sentences such as ‘Bil 
gives John the bok.’ From this, they learn the 
double-object construction: giver + ‘give’ + recipi-
ent + gift.  They also learn the competing item-
based construction of giver + ‘give’ + gift + ‘to’ 
recipient.  There is no need to invoke the Subset 
Principle to explain this learning, since item-based 
constructions are inherently conservative and pro-
vide their own constraints on the form of gram-
mars. Having acquired these two basic 
constructions, children can them join them into a 
single item-based finite automaton that operates on 
narrowly defined lexical categories. 
 
 
 
  
 
 
 
Children can learn this item-based grammar frag-
ment on the basis of simple positive data.  This 
example uses the formalism of a finite-state 
automaton to annotate the use of positive data. 
However, in the Competition Model and other 
conectionist accounts, the two verb frames com-
pete probabilistically with the outcome of the 
competition being determined by further cues such 
as focusing or topicalization. 
Item-based learning involves an ongoing proc-
ess of generalization for the semantic features of 
the arguments. During these processes of generali-
zation, to minimize the posibility of error, the 
child has to be conservative in three ways: 
• The child needs to formulate each syntactic 
combination as an item-based construction. 
giver gives 
gift 
recip 
to recip 
gift 
59
• Each item-based construction needs to record 
the exact semantic status of each positive in-
stance of an argument in a particular gram-
matical configuration (MacWhiney, 1987a). 
• Atempts to use the item-based construction 
with new arguments must be closely guided by 
the semantics of previously encountered posi-
tive instances. 
If the child has a god memory and applies this 
method cautiously, overgeneralization wil be 
minimized and there wil be no need to recover 
from overgeneralization. 
Each item-based construction is linked to a spe-
cific lexical item.  This item must be a predicate. 
There are no item-based constructions for nouns. 
Predicates can have up to three arguments. Item-
based constructions for verbs can also include the 
verbs of embedded clauses as posible arguments. 
Item-based constructions for prepositions and aux-
iliaries include both a phrase internal head (endo-
head) and a head for the phrase attachment 
(exohead). For details on the implementation of 
this grammatical relations model through a parser 
see Sagae, MacWhiney, and Lavie (204).  In 
section 4.6, we wil see how item-based construc-
tions are generalized to feature-based constructions 
in accord with the account of MacWhiney 
(1987a) 
Conservatism also applies to non-local move-
ment patterns.  For example, Wolfe Quintero 
(192) has shown that conservatism can be used to 
account for L2 acquisition of the wh-movement 
patterns. She notes that L2 learners acquire these 
positive contexts for wh-movement in this order: 
32. What did the litle girl hit _ with the block 
today? 
3. What did the boy play with _ behind his 
mother? 
34. What did the boy read a story about _ this 
morning? 
Because they are proceeding conservatively, learn-
ers never produce forms such as (35): 
35. *What did the boy with __ read a story 
this morning? 
They never hear this structure in the input and 
never hypothesize a grammar that includes it. As a 
result, they never make overgeneralizations and 
never attempt wh-movement in this particular con-
text. Data from Maratsos, Kuczaj, Fox & Chalkley 
(1979) show that this same analysis aplies to first 
language learners. 
4.4  Competition 
Conservatism is a powerful mechanism for ad-
dressing the logical problem. However, children 
wil eventually go ‘beyond the information given’ 
and produce errors (Jespersen, 192). When the 
child produces errors, some mechanism must force 
recovery. The four processes that have been pro-
posed by emergentist theory are: competition, cue 
construction, monitoring, and indirect negative 
evidence.  Each of these processes can work to 
correct overgeneralization.  These processes are 
important for adressing the version of the logical 
problem that emphasizes the poverty of negative 
evidence. 
The fourth solution to the problem of poverty of 
negative evidence relies on the mechanism of 
competition. Of the four mechanisms for promot-
ing recovery from overgeneralization, competition 
is the most basic, general, and powerful. Psycho-
logical theories have often made reference to the 
notion of competition. In the area of language ac-
quisition, MacWhiney (1978) used competition to 
account for the interplay between ‘rote’ and ‘anal-
ogy’ in learning morphophonology. Competition 
was later generalized to all levels of linguistic 
processing in the Competition Model. In the 190s, 
specific aspects of learning in the Competition 
Model were formulated through both neural net-
work theory and the ACT-R production system. 
The Competition Model views overgeneraliza-
tions as arising from two types of pressures. The 
first pressure is the underlying analogic force that 
produces the overgeneralization. The second pres-
sure is the growth in the rote episodic auditory 
representation of a correct form. This 
representation slowly grows in strength over time, 
as it is repeatedly strengthened through encounters 
with the input data. These two forces compete for 
the control of production. Consider the case of 
‘*goed’ and ‘went’. The overgeneralization ‘goed’ 
is suported by analogy. It competes against the 
weak rote form ‘went,’ which is suported by 
auditory memory. As the strength of the rote 
auditory form for ‘went’ grows, it begins to win 
out in the competition against the analogic form 
‘*goed’. Finally, the error is eliminated. This is the 
Competition Model account for recovery from 
overgeneralization. The compett between two candidate forms is 
governed by the strength of their episodic auditory 
representations. In the case of the competition be-
60
tween ‘*goed’ and ‘went’, the overgeneralized 
form has litle episodic auditory strength, since it is 
heard seldom if at all in the input. Although 
‘*goed’ lacks auditory suport, it has strong 
analogic suport from the general pattern for past 
tense formation. In the Competition Model, 
analogic pressure stimulates overgeneralization 
and episodic auditory encoding reins it in. The 
analogic pressure hypothesized in this account has 
been described in detail in several conectionist 
models of morphophonological learning. The mod-
els that most closely implement the type of compe-
tition being described here are the models of 
MacWhiney and Leinbach (191) for English and 
Machiney, Leinbach, Taraban & McDonald 
(1989) for German. In these models, there is a 
pressure for regularization according to the general 
pattern that produces forms such as ‘*goed’ and 
‘*ranned’. In addition, there are weaker gang ef-
fects that lead to overgeneralizations such as 
‘*stang’ for the past tense of ‘sting’. 
Competition implements the notion of blocking 
developed first by Baker (1979) and later by Pinker 
(194). Blocking is more limited than competition 
because it requires either strict rule-ordering or all-
or-none competition. The assumption that forms 
are competing for the same meaning is identical to 
the Principle of Uniqueness postulated by Pinker 
(194). Competition is also the general case of the 
Direct Contrast noted by Saxton (197). 
Competition goes beyond the analyses offered 
by Baker, Pinker, and Saxton by emphasizing the 
fact that the child is continually internalizing adult 
forms in episodic memory.  Recent evidence for 
the power of episodic memory in infant audition 
(Aslin et al., 199) has underscored the power of 
neural mechanisms for storing linguistic input and 
extracting patterns from this input without con-
scious processing. The Competition Model as-
sumes that children are continually storing traces 
of the words and phrases they hear along with tags 
that indicate that these phrases derive directly from 
adult input. When the child then comes to produce 
a spontaneous form, these stored forms function as 
an ‘oracle’ or ‘informant’, providing delayed nega-
tive evidence that corresponds (because of compe-
tition or Uniqueness) to the currently generated 
productive form. The ultimate source of this nega-
tive evidence is the input. Children do not use this 
evidence when it is initially presented. It is only 
later when the information is retrieved in the con-
text of productive combinations that it provides 
negative evidence. This can only happen if it is 
clear that stored adult forms compete directly 
(Saxton, 197) with productive child forms. The 
crucial claim of the Competition Model is that the 
same retrieval cues that triger the formation of the 
overgeneralized productive form also triger the 
retrieval of the internalized negative evidence. 
When these assumptions hold, there is a direct so-
lution to the logical problem through the availabil-
ity of internalized negative evidence. 
To gain a better understanding of the range of 
phenomena that can be understod in terms of 
competition, let us lok at examples from mor-
phology. lexical semantics, and syntactic construc-
tions. 
4.4.1 Morphological competition 
Bowerman (1987) argued that recovery from 
overgeneralizations such as ‘*unsqueeze’ is par-
ticularly problematic for a Competition Model ac-
count. She holds that recovery depends on 
processes of semantic reorganization that lie out-
side the scope of competition. To make her exam-
ple fuly concrete, let us imagine that ‘*unsqueeze’ 
is being used to refer to the voluntary opening of a 
clenched fist. Bowerman holds that there is no ob-
vious competitor to ‘*unsqueeze.’ However, when 
presented with this concrete example, most native 
speakers wil say that both ‘release’ and ‘let go’ 
are reasonable alternatives. The Competition 
Model claim is that, because there is no rote audi-
tory suport for ‘*unsqueeze,’ forms like ‘release’ 
or ‘let go’ wil eventually compete against and 
eliminate this particular error. 
Several semantic cues suport this process of 
recovery. In particular, inanimate objects such as 
ruber balls and sponges cannot be ‘*unsqueezed’ 
in the same way that they can be ‘squeezed.’ 
Squeezing is only reversible if we focus on the ac-
tion of the body part doing the squeezing, not the 
object being squeezed. It is posible that, at first, 
children do not fuly apreciate these constraints 
on the reversibility of this particular action. How-
ever, it is equally likely that they resort to using 
‘*unsqueeze’ largely because of the unavailability 
of more suitable competitors such as ‘release.’ An 
error of this type is equivalent to production of 
‘falled’ when the child is having trouble remem-
bering the correct form ‘fell.’ Or consider the 
61
competition between ‘*unapproved’ and its ac-
ceptable competitor  ‘disaproved’. We might 
imagine that a mortgage loan application that was 
initially approved could then be subsequently 
‘*unapproved.’ We might have some uncertainty 
about the reversibility of the aproval process, but 
the real problem is that we have not sufficiently 
solidified our notion of ‘disapproved’ in order to 
have it apply in this case. The flip side of this coin 
is that many of the child’s extensional productions 
of reversives wil end up being acceptable. For ex-
ample, the child may produce ‘unstick’ without 
ever having encountered the form in the input. In 
this case, the form wil survive.  Although it wil 
compete with ‘remove’, it wil also receive occa-
sional suport from the input and wil survive long 
enough for it to begin to carve out further details in 
the semantic scope of verbs that can be reversed 
with the prefix ‘un-’ (Li & MacWhiney, 196). 
4.4.2 Lexical competition 
The same logic that can be used to account for re-
covery from morphological overgeneralizations 
can be used to account for recovery from lexical 
overgeneralizations. For example, a child may 
overgeneralize the word ‘kity’ to refer to tigers 
and lions. The child wil eventually learn the cor-
rect names for these animals and restrict the over-
generalized form. The same three forces are at 
work here: analogic pressure, competition, and 
episodic encoding. Although the child has never 
actually seen a ‘kity’ that loks like a tiger, there 
are enough shared features to license the generali-
zation. If the parent suplies the name ‘tiger.’ there 
is a new episodic encoding that then begins to 
compete with the analogic pressure. If no new 
name is suplied, the child may stil begin to ac-
cumulate some negative evidence, noting that this 
particular use of ‘kity’ is not yet confirmed in the 
input. 
Merriman (199) has shown how the linking of 
competition to a theory of attentional focusing can 
account for the major empirical findings in the lit-
erature on Mutual Exclusivity (the tendency to 
treat each object as having only one name). By 
treating this constraint as an emergent bias, we 
avoid a variety of empirical problems. Since com-
petition is probabilistic, it only imposes a bias on 
learning, rather than a fixed inate constraint. The 
probabilistic basis for competition alows the child 
to deal with hierarchical category structure without 
having to enforce major conceptual reorganization. 
Competition may initially lead a child to avoid re-
ferring to a ‘robin’ as a ‘bird,’ since the form 
‘robin’ would be a better direct match. However, 
sometimes ‘bird’ does not compete directly with 
‘robin.’ This occurs when referring to a colection 
of different types of birds that may include robins, 
when referring to an object that cannot be clearly 
identified as a robin, or when making anaphoric 
reference to an item that was earlier mentioned as a 
‘robin.’ 
4.4.3 Syntactic frame competition 
Overgeneralizations in syntax arise when a feature-
based construction common to a group or ‘gang’ of 
verbs is incorrectly overextended to a new verb. 
This type of overextension has been analyzed in 
both distributed networks (Miikulainen & May-
berry, 199) and interactive activation networks 
(Elman et al., 205; MacDonald et al., 194; 
MacWhiney, 1987b). These networks demon-
strate the same gang effects and generalizations 
found in networks for morphological forms 
(Plunkett & Marchman, 193) and spelling 
correspondences (Taraban & McClelland, 1987). If 
a word shares a variety of semantic features with a 
group of other words, it wil be treated syntacti-
cally as a member of the group. 
Consider the example of overgeneralizations of 
dative movement. Verbs like ‘give’, ‘send’, and 
‘ship’ all share a set of semantic features involving 
the transfer of an object through some physical 
medium. In this regard, they are quite close to a 
verb like ‘deliver’ and the three-argument verb 
group exerts strong analogic pressure on the verb 
‘deliver’. However, dative movement only aplies 
to certain frequent, monosylabic transfer verbs 
and not to multisylabic, Latinate forms with a less 
transitive semantics such as ‘deliver’ or ‘recom-
mend.’ When children overgeneralize and say, 
‘Tom delivered the library the bok,’ they are 
obeying analogic pressure from the group of trans-
fer verbs that permit dative movement. In effect, 
the child has created a new argument frame for the 
verb ‘deliver.’ The first argument frame only 
specifies two arguments – a subject or ‘giver’ and 
an object or ‘thing transferred.’ The new lexical 
entry specifies three arguments. These two homo-
phonous entries for ‘deliver’ are now in competi-
62
tion, just as ‘*goed’ and ‘went’ were in competi-
tion. Like the entry for ‘*goed’, the three-place 
entry for ‘deliver’ has god analogic suport, but 
no suport from episodic encoding derived from 
the input. Over time, it loses in its competition 
with the two-argument form of ‘deliver’ and its 
progressive weakening along with strengthening of 
the competing form leads to recovery from over-
generalization. Thus, the analysis of recovery from 
‘Tom delivered the library the bok’ is identical to 
the analysis of recovery from ‘*goed’. 
4.4.4 Modeling construction strength 
It may be useful to characterize the temporal 
course of competitive item-based learning in 
slightly more formal terms. To do this, we can say 
that a human language is generated by the applica-
tion of a set of constructions that map arguments to 
predicates. For each item-based construction (IC), 
there is a correct maping (CM) from argument to 
its predicates and any number of incorrect map-
pings (IM).  The IMs receive suport from 
analogical relations to groups of CM with similar 
structure. From these emerge feature-based con-
structions (FC). The CMs receive suport from 
positive input, as well as analogical relations to 
other CMs and FCs. Each positive input increases 
the strength S of a matching CM by amount A. 
Learning of an IC occurs when the S of CM ex-
ceeds the S of each of the strongest competing IM 
by some additional amount. This is the dominance 
strength or DS. 
To model language learning within this frame-
work, we need to understand the distribution of the 
positive data and the sources of analogical suport. 
From database searches and calculation of ages of 
learning of CM, we can estimate the number of 
positive input examples (P) needed to bring a CM 
to strength DS. For each C, if the input has in-
cluded P cases by time T, we can say that a par-
ticular CM reaches DS monotonically in time T. 
At this point, IC is learned. Languages are learn-
able if their component ICs can be learned in time 
T. To measure learning to various levels, we can 
specify learning states in which there remain cer-
tain specified slow constructions (SC) that have 
not yet reached DS. Constructions learned by this 
time can be called NC or normal constructions. 
Thus, at time T, the degree of completion of the 
learning of L can be expressed as NC/NC + SC. 
This is a number that approaches 1.0 as T in-
creases.  The residual presence of a few SC, as 
well as occasional spontaneous declines in DS of 
CM wil lead to deviations from 1.0. The study of 
the SCs requires a model of analogic suport from 
FCs. In essence, the logical problem of language 
acquisition is then restated as the process of under-
standing how analogical pressures lead to learning 
courses that deviate from what is predicted by sim-
ple learning on positive exemplars for individual 
item-based constructions. 
4.5  Cue construction 
The fifth solution to the logical problem and the 
second of the solutions that promotes recovery 
from overgeneralization is cue construction. Most 
recovery from overgeneralization relies on compe-
tition. However, competition wil eventually en-
counter limits in its ability to deal with the fine 
details of grammatical patterns. To ilustrate these 
limits, consider the case of recovery from resulta-
tive overgeneralizations such as ‘*I untied my 
shoes lose’. This particular extension receives 
analogic suport from verbs like ‘shake’ or ‘kick’ 
which permit ‘I shok my shoes lose’ or ‘I kicked 
my shoes lose.’ It appears that the child is not 
initially tuned in to the fine details of these seman-
tic classifications. Bowerman (198) has sugested 
that the process of recovery from overgeneraliza-
tion may lead the child to construct new features to 
block overgeneralization.  We can refer to this 
process as ‘cue construction.’ 
Recovering from other resultative overgenerali-
zations may also require cue construction. For ex-
ample, an error such as ‘*The gardener watered the 
tulips flat’ can be attributed to the operation of a 
feature-based construction which yields three-
argument verbs from ‘hammer’ or ‘rake’, as in 
‘The gardener raked the grass flat.’ Source-goal 
overgeneralization can also fit into this framework. 
Consider, ‘*The maid poured the tub with water’ 
instead of ‘The maid poured water into the tub’ 
and ‘*The maid filed water into the tub’ instead of 
‘The maid filed the tub with water.’ In each case, 
the analogic pressure from one group of words 
leads to the establishment of a case frame that is 
incorrect for a particular verb. Although this com-
petition could be handled just by the strengthening 
of the correct patterns, it seems likely that the child 
63
also needs to clarify the shape of the semantic fea-
tures that unify the ‘pour’ verbs and the ‘fil’ verbs. 
Bowerman (personal communication) provides 
an even more challenging example. One can say 
‘The customers drove the taxi driver crazy,’ but 
not ‘*The customers drove the taxi driver sad.’ The 
error involves an overgeneralization of the exact 
shape of the resultative adjective. A conectionist 
model of the three-argument case frame for ‘drive’ 
would determine not only that certain verbs license 
a third posible argument, but also what the exact 
semantic shape of that argument can be. In the case 
of the standard pattern for verbs like ‘drive,’ the 
resultant state must be terminative, rather than 
transient. To express this within the Competition 
Model context, we would need to have a competi-
tion between a confirmed three-argument form for 
‘drive’ and a loser overgeneral form based only 
on analogic pressure. A similar competition ac-
count can be used to account for recovery from an 
error such as, ‘*The workers unloaded the truck 
empty’ which contrasts with ‘The workers loaded 
the truck ful’. In both of these cases, analogic 
pressure seems weak, since examples of such er-
rors are extremely rare in the language learning 
literature. 
The actual modelling of these competitions in a 
neural network wil require detailed lexical work 
and extensive corpus analysis. A sketch of the 
types of models that wil be required is given in 
MacWhiney (199). 
4.6  Monitoring 
The sixth solution to the logical problem involves 
children’s abilities to monitor and detect their own 
errors. The Competition Model holds that, over 
time, correct forms gain strength from encounters 
with positive exemplars and that this increasing 
strength leads them to drive out incorrect forms. If 
we make further assumptions about uniqueness, 
this strengthening of correct forms can guarantee 
the learnability of language. However, by itself, 
competition does not fuly account for the dynam-
ics of language processing in real social interac-
tions. Consider a standard self-correction such as ‘I 
gived, uh, gave my friend a peach.’ Here the cor-
rect form ‘gave’ is activated in real time just after 
the production of the overgeneralization. 
MacWhiney (1978) and Elbers & Wijnen (193) 
have treated this type of self-correction as involv-
ing ‘expressive monitoring’ in which the child lis-
tens to her own output, compares the correct weak 
rote form with the incorrect overgeneralization, 
and attempts to block the output of the incorrect 
form. One posible outcome of expressive moni-
toring is the strengthening of the weak rote form 
and weakening of the analogic forms. Exactly how 
this is implemented wil vary from model to model 
In general, retraced false starts move from incor-
rect forms to correct forms, indicating that the in-
correct forms are produced quickly, whereas the 
correct rote forms take time to activate. Kawamoto 
(194) has shown how a recurent conectionist 
network can simulate exactly these timing asym-
metries between analogic and rote retrieval. For 
example, Kawamoto’s model captures the experi-
mental finding that incorrect regularized pronun-
ciations of ‘pint’ to rhyme with ‘hint’ are produced 
faster than correct irregular pronunciations. 
An even more powerful learning mechanism is 
what MacWhiney (1978) called ‘receptive moni-
toring.’ If the child shadows input structures 
closely, he wil be able to pick up many discrepan-
cies between his own productive system and the 
forms he hears. Berwick (1987) found that syntac-
tic learning could arise from the attempt to extract 
meaning during comprehension. Whenever the 
child cannot parse an input sentence, the failure to 
parse can be used as a means of expanding the 
grammar. The kind of analysis through synthesis 
that occurs in some parsing systems can make 
powerful use of positive instances to establish new 
syntactic frames. Receptive monitoring can also be 
used to recover from overgeneralization. The child 
may monitor the form ‘went’ in the input and at-
tempt to use his own grammar to match that input. 
If the result of the receptive monitoring is ‘*goed’, 
the child can use the mismatch to reset the weights 
in the analogic system to avoid future overgener-
alizations. 
Neural network models that rely on back-
propagation assume that negative evidence is con-
tinually available for every learning trial. For this 
type of model to make sense, the child would have 
to depend heavily on both expresive and receptive 
monitoring. It is unlikely that these two mecha-
nisms operate as continuously as would be re-
quired for a mechanism such as back-propagation. 
However, not all conectionist models rely on the 
availability of negative evidence. For example, 
Kohonen’s self-organizing feature map model 
64
(Miikulainen, 193) learns linguistic paterns 
simply using cooccurences in the data with no reli-
ance on negative evidence. 
4.7  Indirect negative evidence 
The seventh solution to the logical problem of 
language acquisition relies on the computation of 
indirect negative evidence. This computation can 
be ilustrated with the error ‘*goed.’ To construct 
indirect negative evidence in this case, children 
need to track the frequency of all verbs and the 
frequency of the past tense as marked by the regu-
lar ‘-ed.’ Then they need to compute regular ‘-ed’ 
as a percentage of all verbs.   Next they need to 
track the frequency of the verb ‘go’ in all of its 
uses and the frequency of ‘*goed”. To gain a bit 
more certainty, they should also calculate the fre-
quency of a verb like ‘jump’ and the frequency of 
‘jumped.’ With these ratios in hand, the child can 
then compare the ratio for ‘go’ with those for 
‘jump’ or verbs in general and conclude that the 
attested cases of ‘*goed’ are fewer than would be 
expected on the basis of evidence from verbs like 
‘jump.’  They can then conclude that ‘*goed’ is 
ungrammatical. Interestingly, they can do this 
without receiving overt correction. 
The structures for which indirect negative evi-
dence could provide the most useful accounts are 
ones that are learned rather late. These typically 
involve low-error constructions of the type that 
motivate the strong form of the logical problem. 
For example, children could compute indirect 
negative evidence that would block wh-raising 
from object-modifying relatives in sentences such 
as (37). 
36. The police arrested the thieves who were 
carrying the lot. 
37. *What did the police arrest the thieves who 
were carrying? 
38. To do this, they would need to track the 
frequency of sentences such as: 
39. Bil thought the thieves were carrying the 
lot. 
40. What did Bil think the thieves were carry-
ing? 
Noting that raising from predicate complements 
occurs fairly frequently, children could reasonably 
conclude that the absence of raising from object 
modification position means that it is ungrammati-
cal. Coupled with conservatism, indirect negative 
evidence can be a useful mechanism for avoiding 
overgeneralization of complex syntactic structures. 
The item-based acquisition component of the 
Competition Model provides a framework for 
computing indirect negative evidence. The indirect 
negative evidence tracker could note that, although 
‘squeeze’ occurs frequently in the input, 
‘*unsqueeze’ does not. This mechanism works 
through the juxtaposition of a form receiving epi-
sodic suport (‘squeeze’) with a predicted inflected 
form (‘unsqueeze’). 
This mechanism uses analogic pressure to pre-
dict the form ‘*unsqueeze.’ This is the same 
mechanism as used in the generation of ‘*goed.’ 
However, the child does not need to actually pro-
duce ‘*unsqueeze,’ only to hypothesize its exis-
tence. This form is then tracked in the input. If it is 
not found, the comparison of the near-zero strength 
of the unconfirmed form ‘unsqueeze’ with the con-
firmed form ‘squeeze’ leads to the strengthening of 
competitors such as ‘release’ and blocking of any 
attempts to use ‘unsqueeze.’ Although this mecha-
nism is plausible, it is more complicated than the 
basic competition mechanism and places a greater 
requirement on memory for tracking of non-
occurrences. Since the end result of this tracking of 
indirect negative evidence is the same as that of the 
basic competition mechanism, it is reasonable to 
imagine that learners use this mechanism only as a 
fall back strategy, relying on simple competition to 
solve most problems requiring recovery from 
overgeneralization. 
 
 
 
5. Consequences and Conclusions 
This analysis sugests that we should not longer 
speak of language learning as being confined by 
the poverty of positive evidence or negative evi-
dence. Both types of evidence are far more abun-
dant than has been imagined. Nor should we 
assume that recovery from overgeneralization in-
volves a fundamental logical problem. Recovery is 
suported by a set of four powerful processes 
(competition, cue construction, monitoring, and 
indirect negative evidence) that provide redundant 
and complementary solutions to the logical prob-
lem. In addition, we know that alternative charac-
terizations of the nature of the target grammar can 
65
take much of the logical bit out of the logical prob-
lem.  Finally, we have seen that the language ad-
dressed to children is not at all unparsable or 
degenerate, once a few superficial retracing struc-
tures are repaired. 
We have reviewed seven solutions to the logical 
problem that work together to buffer the process of 
language acquisition. When we consider the inter-
action of the seven solutions in this way, we son 
come to realize the pivotal role played by the item-
based construction. First, the item-based construc-
tion directly enforces conservatism by requiring 
that each generalization of each argument frame be 
based on directly observable positive evidence. 
Second, the probabilistic competition between 
item-based constructions provides a meaningful 
way of understanding the probabilistic nature of 
grammar. Third, the competition between item-
based constructions directly promotes recovery 
from overgeneralization.  Fourth, the additional 
mechanisms of cue construction, indirect negative 
evidence, and monitoring serve to fine-tune the 
operations of competition. These processes operate 
particularly in those cases where uniqueness is not 
fuly transparent or where the restriction of a gen-
eral process requires additional fine-tuning of cues. 
The current analysis assigns great importance to 
god positive data. Marcus (193) has sugested 
that parents are inconsistent in their provision of 
negative evidence to the child. But the Competition 
Model assumes that it is positive data that is cru-
cial for learning. One way in which a parent can 
provide crucial positive evidence is through recast-
ing, but other methods are posible to. In various 
cultures and subgroups, positive evidence can be 
presented and focused through elicited repetition, 
choral recitation of stories, interaction with sib-
lings, or games. Methods that emphasize shared 
attention and shared understanding can guide chil-
dren toward the control of literate expression. This 
shared attention can arise in groups of co-wives in 
Central Africa just as easily as it can from isolated 
mother–child dyads in New England. 
Recently, Hauser, Chomsky, & Fitch (202) 
have argued that the core evolutionary adaptation 
that was required to suport human language in-
volved the introduction of a facility for recursion. 
The analysis in the current paper modifies and ex-
tends this claim by emphasizing the evolutionary 
(MacWhiney, 205) and developmental 
(Tomasello, 200) centrality of the item-based 
construction as the controler of recursive composi-
tion of phrases and sentences. However MacWhin-
ney (205) views linguistic recursion as emerging 
gradually from preexisting structures in spatial 
cognition, rather than as appearing sudenly during 
the Late Pleistocene. Studies of the functional neu-
ral underpinings of recursion can go a long ways 
toward clarifying the details of these isues. 
 
Acknowledgements 
 
This work was suported by NSF Grant SBE-
035420 to the Pitsburgh Science of Learning 
Center. 

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