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When adding a little is adding too much: how discourse particles force immediate reanalysis and increase processing costs in under-specific contexts

Published online by Cambridge University Press:  26 August 2025

Pia Järnefelt*
Affiliation:
Department of Scandinavian Languages, Uppsala University , Uppsala, Sweden
Gustaf Gredebäck
Affiliation:
Department of Psychology, Uppsala University , Uppsala, Sweden
Gunnar Norrman
Affiliation:
Centre for Research on Bilingualism, Stockholm University , Stockholm, Sweden
*
Corresponding author: Pia Järnefelt; Email: pia.jarnefelt@nordiska.uu.se
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Abstract

Highly frequent discourse particles (DPs) express speaker attitudes and guide utterance interpretation, but we still lack a satisfactory explanation of how DPs are actually processed. Some results show facilitation, while others show processing costs. Previous studies have aimed to elicit core meanings of DPs embedded in highly plausible contexts, in contrast to more unlikely contexts that force two quite different interpretations. The present study uses a novel eye-tracking experiment where DPs instead are presented in low-constraint contexts. The plausible interpretations consist of two ends of a natural scale: the state change of color that fades or becomes dirty (black to gray or white to gray). This design renders a more direct reflection of how DPs alter context interpretation. Results show that DPs induce immediate reanalysis, and this reanalysis differs in magnitude depending on the kind of DP used. We suggest that the processing of DPs involve three dimensions: i) linguistic intuition about the DP, ii) assumptions about speaker meaning and iii) contextual considerations. The results are interpreted through the communicative principle of language, under-specificity and the maxim of quantity. We also suggest that diverging results from previous studies in the field can be explained using the same analytical lens.

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Type
Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2025. Published by Cambridge University Press
Figure 0

Figure 1. Examples of stimuli. Left: target item, right: filler item.

Figure 1

Figure 2. Experiment design: trial work flow. For each trial, the screen with four objects was displayed while the audio unfolded. Once the audio had played out, a 2000 ms gray screen with a fixation cross was presented. Then the four objects appeared again, and participants were allowed to select an object using the mouse.

Figure 2

Figure 3. Upper panel shows Target and Competitor responses for each condition. Each dot represents the mean of participants, where 1 corresponds to the participant always choosing the Target object, and 0 corresponds to always choosing the Competitor object. The lower panel shows reaction times and individual mean response latencies. Error bars show standard error of the mean.

Figure 3

Figure 4. Log-likelihood of looking toward the Target (black shirt) or the Competitor (gray shirt), in the three different conditions: Adversative (egentligen), Confirmatory (faktiskt) and Adverb (väldigt). 0 on the X-axis marks when the participants heard the word ‘black’ or ‘white’. Positive values indicate more looks toward the Target, and negative values indicate more looks toward the Competitor.

Figure 4

Figure 5. Click-contingent gaze patterns in the Adversative condition when selecting the Target object (Upper panel) or the Competitor object (Lower panel), by participants who consistently selected either the Target object (dashed line) or Competitor object (dotted line), or remained undecisive between the two (solid line). Ribbons show standard error of the mean.

Figure 5

Figure 6. Baseline corrected pupillary responses. Gray boxes indicate sections in time where pupillary responses differ from baseline using cluster-based permutation statistics. Ribbon shows standard error of the mean. 0 on the X-axis corresponds to the point in time when they heard the DP or the adverb.

Figure 6

Figure 7. Pupillary dilation during the fixation period averaged over participants. The star indicates where pupil dilation differs significantly from baseline. Error bars show standard error of the mean.