language researchers
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Hauk et al. (2006)
Typical e.g. lint vs atypical e.g. kiwi (not common in english)- brain able to detect difference that some letter strings are more typical than others
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Stroop (1935)
No difference between reading words in incompatible colours vs. reading words in black ink. - Naming ink colours: Slower responses for ink of incompatible words than for solid colour squares.
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Bisson et al. (2012)
Pay attention to faces when top left Bottom left- standard for forgein language film- initially attend to faces then subtitles when they appear- to understand it they need to read it If bottom right- don’t know any dutch, when have english audio no
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(Forster & Davis, 1984)
Masked nonword prime facilitates target word processing e.g. bontrast - CONTRAST
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Ferrand & Grainger (1993)
masked nonword priming klan and clan-If prime is one letter different it still facilitates the process and makes it faster to recog target
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Perfetti & Tan, 1998)
Semantic overlap at 80-90ms- e.g. doctor, nurse If prime semantically related to target also speeds up the process
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(McClelland & Rumelhart, 1981; Rumelhart & McClelland, 1982)
IA model
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Coltheart et al., 2001
Dual-Route Cascaded (DRC)
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Grainger & Jacobs, 1996
Multiple Read-Out Model
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Coltheart et al. (1977):
Number of words that can be created by changing one letter of a target word- orthographic neighbours target: MINE, neighbours: PINE, LINE, MIND, MINT (N=29)
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Andrews (1989, 1992):
facilitation for neighbourhood size/density
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Andrews (1989, 1992):
null effects of neighbourhood size/density
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Carreiras et al. (1997):
inhibition effects of neighbourhood size/density
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Carreiras et al. (1997), Grainger (1989), Grainger et al. (1990
inhibition of neighbourhood frequency effects
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Andrews (1989, 1992)
naming task facilitation
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Grainger & Jacobs (1996)
variation of IA model Multiple Read-out Model: IA model with decision criteria to ID when someone will make a response Three noisy response criteria: Single word node activity (M) Summed activity of all active words (sigma) Time threshold (T)
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(Andrews, 1996)
Transposition neighbours (SLAT - SALT) Inhibitory effects in LDT (lexical deicision task) and Naming
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Schoonbaert & Grainger, 2003
Transposition priming sevrice primes SERVICE slightly different order in prime still activates the target word itself
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Forster et al., 1987)
identity priming (what - WHAT) and transposition primes (waht - WHAT) produce both the same amount of priming
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Peressotti & Grainger, 1999
silr primes SAILOR if some of letters of target word but in the same order, this will speed up the processing is well
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Seidenberg & McClelland, 1989
Wickelgraphs LEAP: #LE, LEA, EAP, AP#- context of which letters surrounded by will help with the recognition process
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Grainger & van Heuven, 2003
Open bigram coding LEAP: LE, LA, LP, EA, EP Model can account for transposition and relative-position priming effects due to high overlap in open-bigrams between prime and target.
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(Davis, 2011)
Spatial Coding
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., Forster & Chambers, 1973)
Common words (e.g. CAR) are recognised faster than less common words (e.g. ARC)
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Kucera and Francis (1967):
American English- Corpus? Of written material of 1million words and count words and how often they occurred
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van Heuven et al., 2013
SUBTLEX-UK: BBC subtitle frequencies
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Brysbaert & New (2009)
Subtitles better than other frequency norms Word form (e.g. play) frequencies better than lemma frequencies (e.g. sum of play, plays, played, playing)
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Morrison & Ellis (1995):
Frequency effects are AoA effects After matching for AoA no difference between high and low frequency words.
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Zevin and Seidenberg (2002):
Morrison & Ellis (1995) results depend on the quality of frequency norms-
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Brysbaert & Cortese (2011):
AoA effects only accounts for about 7% extra variance in lexical decision times- clearly has some impact but a magnitude smaller than word frequency
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Balota et al., 2007
English Lexicon Project: 40,481 words Non-linear effect – fast from 3-5 letters, then no effect 6,7,8 then get much slower from that point onwards
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Rey et al. (2000)
Graphemes form the bridge between orthography and phonology
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Frost, 1989; Van Orden et al., 1990)
Phonology is automatically activated
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Rubenstein et al. (1971); Coltheart et al. (1977); Ziegler et al. (2001)
Pseudohomophone effect
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Rubenstein et al. (1971); Ferrand & Grainger (2003); Pexman et al. (2001
homophone effect- Priming studies have also shown that phonology is activated rapidly, e.g. koat - COAT vs. poat - COAT.
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Seidenberg et al. ,1984; Stone et al., 1997)
Spelling-to-Sound consistency / regularity effects How the spelling maps to the sound e.g. INT sounds different… -INT is pronounced differently in HINT and PINT- INT not consistent- it is irregular word YACHT is an irregular
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Wilhelm Wundt, 1900
speaking first based on a theory of introspection
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Meringer & Mayer (1896)
collected and analysed for the first time spontaneously produced speech errors
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Miller, 1991)
Mental lexicon contains 50K - 100K words in a normal literate adult
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Levelt, 2001)
Errors: 1 or 2 every 1000 words, speech production process- conceptualisation, formulation and articulation
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Nooteboom, 1969; Fromkin, 1971
Exchanged words belong to the same syntactic category (e.g., verb, noun
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Meyer (1992)
Diagnosis of sound errors depends on listener judgements. Problem of the ambiguity of errors (e.g., shift or deletion). Some classes of errors are hardly ever observed (e.g., intonation, stress), but one need to analyse them to understand phon encod
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Ferber (1991):
Collector's bias Online and offline detection of speech errors Ferber: 51 speech errors 4 listeners online: between 7 and 25 speech errors 14 errors not detected at all none of the errors detected by all listeners 20 errors detected by 1 listener
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Baars, Motley, & MacKay (1975)
phonological bias technique (SLIP: Spoonerisms of Laboratory-Induced Predisposition) Word-Word spoonerisms (e.g., 'barn door'): 32 times Word-Nonword spoonerisms (e.g., 'bart doard'): 10- happening less so
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cont...
Lexical Bias effect Induced sound errors tend to create words however, no lexical bias when items in the list are nonwords Monitoring Users check the lexical status before articulation. No monitoring when items in the list are nonwords- flexible sys
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Dell and Reich (1981)
selected speech errors from a corpus that involved phoneme exchanges (e.g., "pitch fork" -> "fitch pork"; "postal code" -> "coastal pode") Lexical bias in exchanges, anticipations, and perseverations
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Hartsuiker, Anton-Mendéz, Roelstraete, & Costa, 2006
lexical biases also found in Spanish- what is possible when people make speech error, replace letter, by chance created word. Observed what the chance of creating a lexical bias was- chance was much higher in spontaneously produced speech compared to
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Dell’s (1986)
Interactive connectionist model of speech production Semantic, lexical, and phonological representations interact. Units specify the syntactic, morphological, and phonological properties of words. Activation spreads from the sentence level to model
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Levelt's 1989
Conceptual (preverbal message)- intension, what you want to say, not language based Formulator grammatical encoder phonological encoder Articulator Monitor(ing system)
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Levelt, Roelofs, & Meyer (1999); Roelofs (1992, 1997)
Implementation of Levelt's model: WEAVER++ Word Encoding by Activation and VERification
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., van Turennout, Hagoort, & Brown (1998
Lexical access involves two stages 1) Lexical selection, 2) Phonological encoding Evidence for two stages comes from: Speech Errors Tip-of-the-tongue phenomenon Behavioural Experiments Electrophysiological Experiments
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Fay & Cutler (1977)
semantic and form based substitutions
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Elbers, 1985)
ToT seen in 2yo
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Burke et al., 1991)
ToT increases with old age
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Gollan & Acenas, 2004)
ToT increases in bilinguals
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(Brown, 1970
ToT explanation- partial activation hypothesis- info activated not strongly enough to retrieve it
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(Woodworth, 1938
Blocking or interference hypothesis thinking about something else so the word you are looking for it blocked
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Vigliocco, Antonini, & Garret (1997)
Retrieval of grammatical gender is preserved in TOT states
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Badecker, Miozzo & Zanuttini (1995)
Evidence from an Italian person who suffered from word-finding difficulties (anomia). Details of grammatical gender available for words that they could not produce. Thus, access to lemmas but not to phonological forms.
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Schriefers, Meyer, & Levelt (1990)
Lexical access to content words: Two independent and serial ordered stages? First stage: Lemma retrieval (syntactic and semantic properties Second stage: Lexeme retrieval (phonological wordform information
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results
Results of Schriefers et al. (1990) support a two-stage serial model of lexical access. Mixed errors and the Lexical Bias effect must be explained by another theoretical notion such as an output editor or a monitor system.
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van Turennout et al. (1998)
Task involves the production of noun phrases (e.g., "red table") LRP go/no-go paradigm Observe elec activity in motor area before they even move their finger syntactic gender determines the response hand - the word-initial phoneme decision determined
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Caramazza & Miozzo, 1997
TOT data suggest that syntactic and phonological information are independent
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Caramazza's (1997)
model- no lemmas needed interaction between lexical-semantic network syntactic network form network (lexemes
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(Caramazza & Miozzo, 1997).
Subjects are able to retrieve gender and initial phoneme of words in TOT states
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Miceli & Caramazza, 1988
Retrieval of syntactic features is not required to successfully activate the phonological form in brain damaged subjects
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Caramazza & Hillis, 1990)
Brain damaged subjects show grammatical deficits that are modality specific (written vs. oral production)
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Frege (1892)
Sense and its reference are two aspects of the meaning of a linguistic expression.
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Katz & Fodor (1963), Smith, Shoben, & Rips (1974)
Decompositional theory Word meanings best described in terms of sets of bivalent semantic features or semantic markers
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Smith, Shoben, & Rips (1974)
Word meaning can be decomposed into a finite set of primitives which are universal across languages.
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McRae, de Sa, & Seidenberg, 1997
types of semantic features- intercorrelated features or distinctive or distinguishing features
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Hollan (1975)
Showed that simple semantic networks and feature theories were formally equivalent.
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Rips, Smith & Shoben (1975)
Pointed out that formal equivalence does not imply psychological equivalence, i.e. different processing assumptions may results in more or less satisfactory performance models
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Wittgenstein (1953)
What set of necessary and sufficient conditions can be used to define the word 'game'? Lots of characteristics
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Rosch (1973, 1978)
Prototype theory derived from Wittgenstein's (1953) ideas about word meaning, i.e. most words cannot be defined in terms of sets of necessary and sufficient conditions.
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Collins and Quillian, (1969)
More time to look up information higher in the hierarchy
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Landauer & Freedman (1968)
For both positive and negative instances recognition of category membership for large categories took longer than for small categories. Nouns are subcateogry of words- living things even smaller level of nouns- number of instances become smaller
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Conrad (1972)
Cognitive economy only supported by Collins & Quillian (1969). Maybe an artefact of the hierarchies used in their experiments. Some sentneces may be related to the frequency of words using Failure to control for association strengths
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(Rips et al., 1973; Rosch, 1973)
Typicality effects- Robin and ostrich both one level away from bird in hierarchy, but easier to verify 'A robin is a bird' than 'An ostrich is a bird'.- differences cannot be explained by network models
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Rips, Shoben, & Smith (1973)
Contrary to predictions based on dog-mammal-animal hierarchy, it is easier to verify 'A dog is an animal' than 'A dog is a mammal'. Solution: Uncommon or specialised concepts in the hierarchy can be by-passed by additional ISA links
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Collins and Loftus (1975)
spreading activation model- spreading activation model- nodes
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Meyer & Schvaneveldt, 1971
Spreading activation explains why words prime subsequent related words in lexical verification tasks e.g., doctor - nurse vs. table
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(Harris, 1954)
Words with similar meanings are used in similar contexts
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Landauer & Dumais (1997), Landauer et al. (1997)
Latent-Semantic Analysis (LSA)
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Lund & Burgess (1996)
Hyperspace Analogue to Language (HAL)
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Mikolov et al., (2013)
Continuous bag of words (CBOW)
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(Mikolov et al.,2013)
Predict target words based on context words. Method uses a neural network that learns from large corpora
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Mandera et al. (2017)
Similarity measure involves using the weights from input nodes to the hidden units (e.g., 300) of word pairs (cosine distance).
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Barsalou et al., 2003).
grounding conceptual knowledge in modality specific systems
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van Berkum et al. 1999
When word doesn’t fit with wider story even if it fits sentence Harder to integrate slow in becaude doesn’t make sense discourse incongruity
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Kutas & Hillyard, 1980
bigger N400 when incongruous
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(Hagoort, Brown, & Groothusen, 1993)
Subject-verb agreement The spoilt child throws / throw the toy on the ground gives you a p600 thats larger if uses throws because it doesnt fit
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(Osterhout, Holcomb, & Swinney, 1994)
Syntactic ‘garden path’ sentences The professor saw (that) the student would succeed
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Harnad, 1990
symbol grounding problem- linking to abstract representation of word with what it actually links to in the world – Chinese dictionary example
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(Barsalou, 1999)
Represent language in terms of own experiences in world Simulate previous experiences of when taking doggo for a stroll
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Stanfied & Zwaan (2001)
Visual orientation- Participants should mentally represent the orientation of the pencil, based on their experiences. RT faster when match orientation implied by sentence
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Zwaan, Stanfield, & Yaxley, 2002
Object shape Mary saw the egg in the eggbox. sentence picture verification tasks- Suggest mental rep perceptual image of objects being described
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Yaxley & Zwaan, 2007)
visibility- moose through clean or dirty goggles Representing images of the envi the object was in- detailed representation
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Wassenburg & Zwaan, 2010
eye-tracking- word-picture verifi task- toothbrush, filler mental rotation task 15-20m First pass reading times longer when orientation mismatched picture they had previously seen
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Coppens, Gootjes, & Zwaan, 2012)
ERPs w-p verifi task ironing board, emotional stroop based task 15m if picture mismatches sentence larger n400
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Hauk, Johnsrude, & Pullvermüller, 2004
fmri Scanned brains whilst reading action words Congruent areas to the actual movement
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Raposo et al. 2009
Literal- same brain activation as when actually performing these actions not when idiomatic
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Glenberg & Kaschak (2002)
If you had mentally simulated direction – if it clashes with actual movement you make= slower who handing who the notebook action-sentence compatibility effect same with who told who the story
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Zwaan, Taylor, & de Boer (2010)
made a story appear phrase-by-phrase by turning a dial. Half of the participants advance the story by turning the dial clockwise, and half by turning it anticlockwise
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Casasanto, 2009)
body specificity hypothesis
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Willems, Hagoort, & Casasanto, 2010).
Brain activity when participants imagine performing actions with their hands - Similar activity observed when reading action verbs
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Casasanto (2011)
right handed gestures more so when saying positive things
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Holt & Beilock, 2006
Ice hockey experts and novices read sentences describing hockey and non-hockey situations. action and expertise. Nonhockey- longer to say yes to things that didn’t match representation e.g. ballon in air vs bag - novice made no difference
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Just and Carpenter (1980)
incremental interpretation: “readers interpret a word while they are fixating it, and they continue to fixate it until they have processed it as far as they can” (p30).
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MacDonald, Pearlmutter, and Seidenberg (1994)
the communicative goal of the listener can be achieved with only a partial analysis of the sentence,” however they viewed “these as degenerate cases.” (p. 686).
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Sanford and Sturt (2002)
incomplete semantic commitment- radio in selfridges thing
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Cristianson, Hollingworth, Halliwell, & Ferreira, 2001)
garden path sentences- while Anna dressed the baby played with the doll. Suggests that once interpretation is “good enough”, people don’t bother clearing up the details.
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Ferreira, 2003
pragmatic normalisation- Active sentences The dog bit the man (99% accurate) man bit dog (99%) passive sentences The man was bitten by the dog (88% accurate) dog bitten by man (74%) – pragmatic knowledge override semantic interpretation processes
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Barton & Sanford, 1993)
survivors problem dont see survivors because the rest of the possible words dont have alive as part of their core meaning - relevant core meaning may aid detection. Air crash (33% detection rate bicycle crash (80%)
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Kutas & Hillyard, 1980)
easy to detect anomalies - He spread the warm bread with socks
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(Erickson & Mattson, 1981)
hard to detect anomalies- moses illusion
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Bohan and Sanford (2008)
monitored people’s eye movements as they read sentences containing hard-to-detect anomalies. comm with hostages, nego with hostages detected vs not not a case of non-reporting but hadnt detected at all- supports shallow processing hyp
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Sanford, Leuthold, Bohan, and Sanford (2011)
same as above experiment but with ERPs- No N400 effect for hard-to-detect anomalies Late positive potential (LPP) effect for hard-to-detect anomalies But ONLY when they were actually detected
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Baker & Wagner, 1987
Subordinate clause- not in focus of attention so less likely to spot it – processes it with less depth Main- more likely to spot it
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Bredart & Modolo, 1988
linguistic focus on animals or moses,
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Sturt, Sanford, Stewart, & Dawydiak, 2004
Key word focussed or not- see if this makes you more likely to detect the change If process more deeply when in focus more likely to detect change More likely to spot cider to beer when in focus
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Sturt et al. 2004
Discourse focus- set question up in text Related hat- cap = more likely notice when info put in focus by discourse- 2 replications of the same finding really Unrelated hat- dog = easy to detect change
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Bredart & Doquier, 1989)
MOSES decided to take two animals of each kind on the Ark (86.5% detection). Moses decided to take TWO animals of each kind on the Ark (68.3% detection).
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Sanford, Sanford, Molle & Emmott, 2006
Text change detection: Critical word presented in Italics or stressed vocally more likely to detect changes- very obvious method though Auditory change detection: Vocal stress on the critical word
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Other cards in this set
Card 2
Front
Stroop (1935)
Back
No difference between reading words in incompatible colours vs. reading words in black ink. - Naming ink colours: Slower responses for ink of incompatible words than for solid colour squares.
Card 3
Front
Bisson et al. (2012)
Back
Card 4
Front
(Forster & Davis, 1984)
Back
Card 5
Front
Ferrand & Grainger (1993)
Back
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