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Abstract

Previous literature has indicated conflicting results regarding a response time bias favouring words indicating large real-world objects (RWO) over words indicating small RWO during a lexical decision task. This study aimed to replicate an original experiment and, expanding on it, disentangle possible alternatives for why this effect is sometimes observed and sometimes not. The same methods as the original study were followed, and the results were inconsistent with all previously published findings. Although no significant difference was observed for response time, the findings indicated a significant difference in accuracy and inverse efficiency scores such that “large” words were recognised significantly more accurately than “small” words. After examining several linguistic dimensions that may also contribute to response time, statistical models accounting for these dimensions yielded a significant and increased effect size for the response time size rating of words in our sample from the United States. Our findings indicate that there is a cognitive bias favouring words representing large RWO over small ones but suggest several additional linguistic factors need to be controlled for it to be detected consistently in response time.

Keywords

Reading language processing psycholinguistics linguistics semantic biases lexical decision task

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References

Balota

D. A.

Yap

M. J.

Cortese

M. J.

Hutchison

K. A.

Kessler

Loftis

Neely

J. H.

Nelson

D. L.

Simpson

G. B.

Treiman

(2007). The English lexicon project. Behavior Research Methods, 39(3), 445–459. https://doi.org/10.3758/BF03193014

Bates

Mächler

Bolker

Walker

(2015). “Fitting Linear Mixed-Effects Models Using lme4.” Journal of Statistical Software, 67(1), 1–48. https://doi.org/10.18637/jss.v067.i01.

Bruyer

Brysbaert

(2011). Combining speed and accuracy in cognitive psychology: Is the inverse efficiency score (IES) a better dependent variable than the mean reaction time (RT) and the percentage of errors (PE)? Psychologica Belgica, 51(1), 5–13. https://doi.org/10.5334/pb-51-1-5

Brysbaert

Keuleers

Mandera

(2019). Recognition times for 54 thousand Dutch words: Data from the Dutch Crowdsourcing Project. Psychologica Belgica, 59(1), 281–300. https://doi.org/10.5334/pb.491

Colombo

Pasini

Balota

D. A.

(2006). Dissociating the influence of familiarity and meaningfulness from word frequency in naming and lexical decision performance. Memory and Cognition, 34(6), 1312–1324. https://doi.org/10.3758/BF03193274

Damian

M. F.

(2010). Does variability in human performance outweigh imprecision in response devices such as computer keyboards? Behavior Research Methods, 42(1), 205–211. https://doi.org/10.3758/BRM.42.1.205

Doyle

A. W.

(2019). Deriving meaning from print: The role of sensorimotor information and context in semantic processing. https://prism.ucalgary.ca/handle/1880/109450

Faul

Erdfelder

Buchner

Lang

A.-G.

(2009). Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses. Behavior Research Methods, 41(4), 1149–1160. https://doi.org/10.3758/BRM.41.4.1149

Heard

Madan

C. R.

Protzner

A. B.

Pexman

P. M.

(2019). Getting a grip on sensorimotor effects in lexical–semantic processing. Behavior Research Methods, 51(1), 1–13. https://doi.org/10.3758/s13428-018-1072-1

10.

Kang

S. H. K.

Yap

M. J.

Tse

C. S.

Kurby

C. A.

(2011). Semantic size does not matter: “Bigger” words are not recognized faster. Quarterly Journal of Experimental Psychology, 64(6), 1041–1047. https://doi.org/10.1080/17470218.2011.575947

11.

Khaligh-Razavi

S. M.

Cichy

R. M.

Pantazis

Oliva

(2018). Tracking the spatiotemporal neural dynamics of real-world object size and animacy in the human brain. Journal of Cognitive Neuroscience, 30(11), 1559–1576. https://doi.org/10.1162/jocn_a_01290

12.

Konkle

Oliva

(2012). A real-world size organization of object responses in occipitotemporal cortex. Neuron, 74(6), 1114–1124. https://doi.org/10.1016/j.neuron.2012.04.036

13.

Koo

T. K.

M. Y.

(2016). A guideline of selecting and reporting intraclass correlation coefficients for reliability research. Journal of Chiropractic Medicine, 15(2), 155–163. https://doi.org/10.1016/j.jcm.2016.02.012

14.

Lexico. (n.d.). Rocket. https://www.dictionary.com/browse/rocket

15.

Kuznetsova

Brockhoff

Christensen

RHB

. (2017). “lmerTest Package: Tests in Linear Mixed Effects Models.” Journal of Statistical Software, 82(13), 1–26. https://doi.org/10.18637/jss.v082.i13.

16.

MacKinnon

D. P.

Krull

J. L.

Lockwood

C. M.

(2000). Equivalence of the mediation, confounding and suppression effect. Prevention Science, 1(4), 173–181. https://doi.org/10.1023/A:1026595011371

17.

Maltz

M. V.

Stubbs

K. M.

Quinlan

D. J.

Rzepka

A. M.

Martin

J. R.

Culham

J. C.

(2021). Familiar size affects the perceived size and distance of real objects even with binocular vision. Journal of Vision, 21(10), 21. https://doi.org/10.1167/jov.21.10.21.

18.

Mandera

Keuleers

Brysbaert

(2020). Recognition times for 62 thousand English words: Data from the English Crowdsourcing Project. Behavior Research Methods, 52(2), 741–760. https://doi.org/10.3758/s13428-019-01272-8

19.

Richardson

J. T. E.

(1975). Imagery, concreteness, and lexical complexity. Quarterly Journal of Experimental Psychology, 27(2), 211–223. https://doi.org/10.1080/14640747508400481

20.

Scott

G. G.

Keitel

Becirspahic

Yao

Sereno

S. C.

(2019). The Glasgow Norms: Ratings of 5,500 words on nine scales. Behavior Research Methods, 51(3), 1258–1270. https://doi.org/10.3758/s13428-018-1099-3

21.

Sereno

S. C.

O’Donnell

P. J.

(2009). Participant and word gender in age of acquisition effects: The role of gender socialization. Sex Roles, 61(7–8), 510–518. https://doi.org/10.1007/s11199-009-9649-x

22.

Sereno

S. C.

O’Donnell

P. J.

Sereno

M. E.

(2009). Size matters: Bigger is faster. Quarterly Journal of Experimental Psychology, 62(6), 1115–1122. https://doi.org/10.1080/17470210802618900

23.

Vuorre

Bolger

(2018). Within-subject mediation analysis for experimental data in cognitive psychology and neuroscience. Behavior Research Methods, 50(5), 2125–2143. https://doi.org/10.3758/s13428-017-0980-9

24.

Yao

Taylor

J. E.

Sereno

S. C.

(2022). What can size tell us about abstract conceptual processing? Journal of Memory and Language, 127, Article 104369. https://doi.org/10.1016/j.jml.2022.104369

25.

Yao

Vasiljevic

Weick

Sereno

M. E.

O’Donnell

P. J.

Sereno

S. C.

(2013). Semantic size of abstract concepts: It gets emotional when you can’t see it. PLoS ONE, 8(9), 2–11. https://doi.org/10.1371/journal.pone.0075000

26.

Yao

Wang

Zhu

Guo

Wang

(2016). Effects of valence and arousal on emotional word processing are modulated by concreteness: Behavioral and ERP evidence from a lexical decision task. International Journal of Psychophysiology, 110, 231–242. https://doi.org/10.1016/j.ijpsycho.2016.07.499

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Bigger is really better: Resolution of conflicting behavioural evidence for semantic size bias in a lexical decision task

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