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Just do it! Colin Phillips Dept of Linguistics Cogn. Neurosci. of Language Lab University of Maryland.

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Presentation on theme: "Just do it! Colin Phillips Dept of Linguistics Cogn. Neurosci. of Language Lab University of Maryland."— Presentation transcript:

1 Just do it! Colin Phillips Dept of Linguistics Cogn. Neurosci. of Language Lab University of Maryland

2 “As for my own methods of investigation, I do not really have any. The only method of investigation is to look hard at a serious problem and try to get some ideas as to what might be the explanation for it, meanwhile keeping an open mind about all sorts of other possibilities. Well, that is not a method. It is just being reasonable.” (Chomsky 1988, p. 190) Does the title reflect a deep philosophical point? …perhaps Feyerabend’s “Anything goes”? Not really… nike.co.jp “Dice-K”

3 Hajime’s 2 questions… 1.“What aspects of language are expected to be analyzable, and to what extent? I.e., what is the object of explanation for linguistic research?” 2.“How can linguistic research make progress?”

4 Linguistics: The Real-time Nature of Linguistic Computation Psycholinguistics: The Linguistic Sophistication of Real-time Computation Cognitive Neuroscience: Using Real-time Brain Recordings to Understand Linguistic Computation Computational Neuroscience: Neural Modeling of Linguistic Computation Answer 1: linguistic computation at all levels

5 Answer 2 Explicit linking hypotheses Theoretical elegance Language variation + language learning (what to do with microvariation) More systematic judgment data

6 Acceptability Judgment Studies Careful controls –Minimal pairs –Plausibility controls –Latin square designs Many items (guide: at least 3 x number of conditions) Many participants (guide: is usually plenty) Fun with statistics! Where’s the action? –Dependent measure: no big deal (scalar rating, Magnitude Estimation, …) –Materials are a huge deal, including filler items –Participants’ understanding of the task –For much discussion & data cf. Jon Sprouse 2007 PhD thesis

7 Japanese (a)soko (Hoji 1991, 1995, Ueyama, 1999) Dono-kaisya-mo soko-no kogaisya-o suisensita. every-company-mo soko-gen subsidiary-acc recommended ‘Every company i recommended its i subsidiary.’ *Dono-kaisya-mo asoko-no kogaisya-o suisensita. every-company-mo asoko-gen subsidiary-acc recommended ‘*Every company i recommended its i subsidiary.’ Reconstruction effects Soko-no kogaisya-o dono-kaisya-mo suisensita. soko-gen subsidiary-acc every-company-mo recommended ‘Every company i recommended its i subsidiary.’ Asoko-no kogaisya-o dono-kaisya-mo suisensita. Asoko-gen subsidiary-acc every-company-mo recommended ‘*Every company i recommended its i subsidiary.’

8 Acceptability Rating Study II. Acceptability rating study (n = 48) Context: A president and his secretary are discussing the current business situations of automobile companies. The president says, … (A)Simbunkiji-niyoruto, [soko i -no itiban yakunitatanai yakuin]-o Newspapers-by soko-gen most useless executive-acc [dono jidoosyagaisya i ]-mo kubinisita toiu hookoku-ga dehajimeta-rasii. every automobile company-mo fired that report-nom appeaedr-seem ‘ The newspaper says that there appears a report that to its most useless employee, every automobile company fired. ’ (B)*Simbunkiji-niyoruto, [soko i -no itiban yakunitatanai yakuin]-ga Newspapers-by soko-gen most useless executive-acc [dono jidoosyagaisya i ]-mo uttaeta toiu hookoku-ga dehajimeta-rasii. every automobile company-mo sued that report-nom appeaedr-seem ‘ The newspaper says that there appears a report that its most useless employee sued every automobile company. ’ ACC-NOM order NOM-ACC order Aoshima, Yoshida, & Phillips in press, Syntax

9 Claim 1: Judgment data is a major impediment to progress Claim 3: Asymmetry * sentencesuniformly judged BAD ok sentencesmixed GOOD and BAD judgments Claim 2: Explicit model of acceptability judgments Ueyama 2007

10 1. Are Judgment Data Hurting Us? Careful judgment experiments yield few surprises –Sentences with parasitic gaps just as good as sentences without (Phillips 2006, Language; Wagers & Phillips, submitted) –Effects of Condition C across various contexts (Kazanina, Lau, Lieberman, Yoshida & Phillips 2007, J. of Memory & Language) –etc., etc. Major theoretical choices are disconnected from empirical details (surprisingly) Need p <.05 ?Ask 6 friends! (1/2 5 = 0.03)

11 Ueyama 2007 Townsend & Bever Is the Judgment Model Correct? It is very hard to find evidence of computation distinct from parsing & production that yields different judgments, different interpretations.

12 Immediate Grammaticality Effects In reading-time and event-related brain potential studies, we (and many others) find almost immediate sensitivity to grammatical contrasts (delays measured in hundreds of milliseconds) –Constraints on movement (English, Japanese, Spanish) –Constraints on anaphora (English, Japanese, Russian) –Agreement (English, Hindi) –Case dependencies in split-ergative languages (Hindi) –Phrase structure constraints (Japanese, Basque) Sometimes we find that on-line measures provide clearer contrasts than acceptability ratings!

13 Acceptability Rating Study II. Acceptability rating study (n = 48) Context: A president and his secretary are discussing the current business situations of automobile companies. The president says, … (A)Simbunkiji-niyoruto, [soko i -no itiban yakunitatanai yakuin]-o Newspapers-by soko-gen most useless executive-acc [dono jidoosyagaisya i ]-mo kubinisita toiu hookoku-ga dehajimeta-rasii. every automobile company-mo fired that report-nom appeaedr-seem ‘ The newspaper says that there appears a report that to its most useless employee, every automobile company fired. ’ (B)*Simbunkiji-niyoruto, [soko i -no itiban yakunitatanai yakuin]-ga Newspapers-by soko-gen most useless executive-acc [dono jidoosyagaisya i ]-mo uttaeta toiu hookoku-ga dehajimeta-rasii. every automobile company-mo sued that report-nom appeaedr-seem ‘ The newspaper says that there appears a report that its most useless employee sued every automobile company. ’ ACC-NOM order NOM-ACC order Aoshima, Yoshida, & Phillips in press, Syntax

14 soko-no syain dono kacyoo dono kaisya INCONGRUOUS CONGRUOUS its employee every manager every company Scrambled ACC-NOM Order Canonical NOM-ACC Order

15 3. No Judgment Asymmetry Hoji & Ueyama claim… –* sentencesuniformly judged BAD –ok sentencesmix of BAD and GOOD judgments Challenge A: when uniformly bad doesn’t entail ungrammatical (island constraints) Challenge B: when mixed good/bad judgments does not entail grammaticality (agreement)

16 3A. Islands

17 Long-distance Wh-Questions Few people think that anybody realizes that Englishmen cook wonderful dinners

18 Long-distance Wh-Questions Few people think that anybody realizes that Englishmen cook what

19 Long-distance Wh-Questions What do few people think that anybody realizes that Englishmen cook gap 

20 Island Constraints What do Few people believe anybody who claims that Englishmen cook what

21 Island Constraints What do Few people believe anybody who claims that Englishmen cook what Relative Clause

22 Island Constraints What do few people believe anybody who claims that Englishmen cook gap Relative Clause

23 Island Constraints What do few people believe anybody who claims that Englishmen cook gap  Relative Clause

24 Island Constraints *Who did the candidate read a book that praised ___? [relative clause island] *Who did the candidate read The Times ’ article about ___? [complex NP island] *Who did the candidate wonder whether the press would denounce ___? [wh-island] *Why did you remember that the senator supported the bill ___? [factive island] *Who did the fact that the candidate supported ___ upset voters in Florida? [subject island] *Who did the candidate raise two million dollars by talking to ___? [adjunct island] Standard Conclusion: wh-movement must be local

25 Island Judgments are Well-behaved from Sprouse 2007, PhD UMd now at UC Irvine Cogn. Science Phillips 2006 Judgments are stable across methods, items, contexts, repetitions, etc. Ratings vary across island types, but they’re reliably judged BAD

26 * Which school did the proposal to expand __ ultimately overburden the teachers?

27 (Phillips, Kazanina, & Abada, 2005) Length Matters

28 A Common Inference Grammatical generalization: wh-dependencies are local Parsing generalization(s): local wh-dependencies are easier/preferred ERGO… perhaps the grammatical generalization derives from the parsing generalization (Fodor 1978; Berwick & Weinberg 1984; Deane 1991; Pritchett 1991; Kluender & Kutas 1993; Hawkins 1999; Sag et al. 2005; Maratsos & Kowalsky 2005) –Variant I: locality constraints are nevertheless grammaticized –Variant II: locality constraints in grammar are epiphenomenal Fodor WeinbergBerwickKluenderHawkins Sag Maratsos

29 Fact: subject islands consistently judged BAD Theory 1: subject island violations are ungrammatical (standard analysis in syntactic theory) Theory 2: subject island effects are consequences of specific language processing mechanisms (various proposals, e.g., Deane 1991, Pritchett 1991, Hawkins 1998, Kluender 2004, etc.) * Which school did the proposal to expand __ ultimately overburden the teachers? ok Which school did the proposal to expand __ ultimately overburden __? Which students … plausibility effect at verb inside island argues against reductionist account of subject islands Phillips 2006, Language

30 3B. Agreement Ellen LauMatt Wagers (Wagers, Lau, & Phillips, 2007)

31 The musicians who the reviewer praise will likely win a Grammy. Many speakers perceive as surprisingly GOOD Grammatical accounts: Kimball & Aissen (1971), Kayne (1989), den Dikken (2001), Baker (2005)

32 Speeded acceptability Relative clauses: SG Subject p < 0.10 *** N = 16 The musician who the reviewer praise … The musicians who the reviewer praise …

33 Self-paced reading study (#2 of 6) SG The musician who the reviewer praises/praise so highly will likely … PL PL The musicians who the reviewer praises/praise so highly will likely …

34 The musicians who the reviewer praise will likely win a Grammy. Many speakers perceive as surprisingly GOOD Grammatical accounts: Kimball & Aissen (1971), Kayne (1989), den Dikken (2001), Baker (2005) Mixed judgments entail grammaticality (Hoji & Ueyama 2007) BUT… “This is just parsing”, “It’s important to train the informants” Doesn’t work for agreement: informants go into ‘copy editor mode’ So what can we do…?

35 Agreement attraction The sheer weight SG of all these facts and figures PL make PL them hard for anyone to understand. (Ronald Reagan; 13 Oct, 1982)

36 SG VP Mechanisms Prediction-failure cued retrieval PL SG NP PP N PNP weight ofthe figures SG weight. SG figures. PL + VP V make PL *

37 Arguments against a Grammatical Account Document parallels with other agreement attraction effects (speeded acceptability studies, reading-time studies) –Grammatical asymmetry (ungrammatical AGR improved, grammatical AGR not reduced) –Singular/plural asymmetry (plurals attract, singulars do not) –Probabilistic nature of the errors –Implicit assumption: surely The weight of the figures make … is bad The musicians who the reviewer praise will likely win a Grammy.

38 Speeded acceptability Relative clauses: SG Subject p < 0.10 *** N = 16 The musician who the reviewer praise … The musicians who the reviewer praise …

39 Speeded acceptability Complex Subjects n.s.** N = 16 The weight of the figure make … The weight of the figures make …

40 Speeded acceptability Relative clauses: PL Subject N = 16 The musician who the reviewers praises … The musicians who the reviewers praises …

41 Arguments against a Grammatical Account Document parallels with other agreement attraction effects (speeded acceptability studies, reading-time studies) –Grammatical asymmetry (ungrammatical AGR improved, grammatical AGR not reduced) –Singular/plural asymmetry (plurals attract, singulars do not) –Probabilistic nature of the errors –Implicit assumption: surely The weight of the figures make … is bad Independently-motivated account based on retrieval failure avoids the need to complicate a simple grammatical generalization The musicians who the reviewer praise will likely win a Grammy.

42 Summary Agree… –Careful data collection is a Good Thing (but the sky is not falling) –Explicit models of judgments are a Really Great Thing Disagree… –Data collection methods are not our biggest challenge –It’s hard to find evidence for a ‘two-derivation’ model of judgments –We can’t make hard-and-fast rules for inferring grammaticality from acceptability The broader picture … –Let’s be serious about notions like Mental Computation

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