2018
DOI: 10.1075/tcb.00001.mel
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Order effects in the translation process

Abstract: This study investigates how the order in which various translation memory match-types occur in a target language version of a text may influence translator behavior and cognition. Empirical research designs often attempt to mitigate for possible confounds from order effects, yet explicit recognition of the time-series nature of data collection can yield a better understanding of the influence that translation technologies have on the translation task. Data are drawn from a previous study that investigated tech… Show more

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Cited by 5 publications
(4 citation statements)
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“…To analyse the data and assess whether the effect of directionality is significant, linear mixed models (LMM) were used for inferential statistics with translation direction and text type as fixed factors and participants and proofreaders as random factors. As observed by Mellinger & Hanson (2018), LMMs are able to account for the individual differences between participants-in this study between the translators and proofreaders.…”
Section: Research Questions and Data Analysismentioning
confidence: 55%
See 1 more Smart Citation
“…To analyse the data and assess whether the effect of directionality is significant, linear mixed models (LMM) were used for inferential statistics with translation direction and text type as fixed factors and participants and proofreaders as random factors. As observed by Mellinger & Hanson (2018), LMMs are able to account for the individual differences between participants-in this study between the translators and proofreaders.…”
Section: Research Questions and Data Analysismentioning
confidence: 55%
“…Translators came for individual sessions and spent on average two hours to do the experimental tasks. The translation direction was counterbalanced and the texts were randomised to minimise task order effects (Mellinger & Hanson 2018).…”
Section: Participants Materials Proceduresmentioning
confidence: 99%
“…In quantitative analysis, linear mixed-effects models (LMEMs), which can compensate for weak control of variables in naturalistic translation tasks ( Saldanha and O’Brien, 2014 ), were employed as one of the analytical techniques to account for high variability among participants and increase the power of tests ( Mellinger and Hanson, 2018 ). We built four LMEMs altogether.…”
Section: Methodsmentioning
confidence: 99%
“…The texts were balanced in terms of their Gunning Fog readability scores (14.1 for the English texts and 14.2 for the Polish pair). Task order was counterbalanced and the order of texts was randomised to minimise the spill over effects (Mellinger and Hanson 2018). All our participants were dominant in Polish, their L1, but also highly proficient in English.…”
Section: Participants Materials Proceduresmentioning
confidence: 99%