Replication Data for: What the MIPVU protocol doesn’t tell you (even though it really does) (doi:10.18710/F04UW5)

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Replication Data for: What the MIPVU protocol doesn’t tell you (even though it really does)

doi:10.18710/F04UW5

DataverseNO

2019-06-28

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Nacey, Susan; Krennmayr, Tina; Dorst, Aletta G.; Reijnierse, W. Gudrun, 2019, "Replication Data for: What the MIPVU protocol doesn’t tell you (even though it really does)", https://doi.org/10.18710/F04UW5, DataverseNO, V1

Replication Data for: What the MIPVU protocol doesn’t tell you (even though it really does)

doi:10.18710/F04UW5

Nacey, Susan (Inland Norway University of Applied Sciences)

Krennmayr, Tina (Vrije Universiteit Amsterdam)

Dorst, Aletta G. (Leiden University)

Reijnierse, W. Gudrun (Radboud University Nijmegen)

Inland Norway University of Applied Sciences

DataverseNO

Inland Norway University of Applied Sciences

Nacey, Susan

Khosrowjerdi, Mahmood

2019-06-14

https://doi.org/10.18710/F04UW5

Arts and Humanities, Metaphor Identification Procedure Vrije Universiteit (MIPVU), Language, inter-rater reliability

<p>The two datasets provided here were used to provide inter-rater reliability statistics for the application of a metaphor identification procedure to texts written in English. Three experienced metaphor researchers applied the Metaphor Identification Procedure Vrije Universiteit (MIPVU) to approximately 1500 words of text from two English-language newspaper articles.</p> <p>The dataset Eng1 contains each researcher’s independent analysis of the lexical demarcation and metaphorical status of each word in the sample.</p> <p>The dataset Eng2 contains a second analysis of the same texts by the same three researchers, carried out after a comparison of our responses in Eng 1 and a troubleshooting session where we discussed our differences. The accompanying R-code was used to produce the three-way and pairwise inter-rater reliability data reported in Section 3.2 of the chapter: How do I determine what comprises a lexical unit?</p> <p>The headings in both datasets are identical, although the order of the columns differs in the two files. In both datasets, each line corresponds to one orthographic word from the newspaper texts.</p>

<p>Chapter Abstract:</p> <p>The first part of this chapter discusses various ‘nitty-gritty’ practical aspects about the original MIPVU intended for the English language. Our focus in these first three sections is on common pitfalls for novice MIPVU users that we have encountered when teaching the procedure. First, we discuss how to determine what comprises a lexical unit (section 3.2). We then move on to how to determine a more basic meaning of a lexical unit (section 3.3), and subsequently discuss how to compare and contrast contextual and basic senses (section 3.4). We illustrate our points with actual examples taken from some of our teaching sessions, as well as with our own study into inter-rater reliability, conducted for the purposes of this new volume about MIPVU in multiple languages. Section 3.5 shifts to another topic that new MIPVU users ask about – namely, which practical tools they can use to annotate their data in an efficient way. Here we discuss some tools that we find useful, illustrating how we utilized them in our inter-rater reliability study. We close this part with section 3.6, a brief discussion about reliability testing.</p> <p>The second part of this chapter adopts more of a bird’s-eye view. Here we leave behind the more technical questions of how to operationalize MIPVU and its steps, and instead respond more directly to the question posed above: Do we really have to identify every metaphor in every bit of our data? We discuss possible approaches for research projects involving metaphor identification, by exploring a number of important questions that all researchers need to ask themselves (preferably before they embark on a major piece of research). Section 3.7 weighs some of the differences between quantitative and qualitative approaches in metaphor research projects, while section 3.8 talks about considerations when it comes to choosing which texts to investigate, as well as possible research areas where metaphor identification can play a useful role. We close this chapter in section 3.9 with a recap of our ‘take-away’ points – that is, a summary of the highlights from our entire discussion.</p>

Written discourse

Nacey, S., Krennmayr,T., Dorst, A.G. & Reijnierse W.G. (2019). What the MIPVU protocol doesn’t tell you (even though it really does). In S. Nacey, A.G. Dorst, T. Krennmayr & W.G. Reijnierse (Eds.), Metaphor identification in multiple languages: MIPVU around the world. Amsterdam: John Benjamins.

10.1075/celcr.22.03nac

Nacey, S., Krennmayr,T., Dorst, A.G. & Reijnierse W.G. (2019). What the MIPVU protocol doesn’t tell you (even though it really does). In S. Nacey, A.G. Dorst, T. Krennmayr & W.G. Reijnierse (Eds.), Metaphor identification in multiple languages: MIPVU around the world. Amsterdam: John Benjamins.

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00_ReadMe.txt

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The description of the data

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Eng1.R

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R code for Eng1

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Eng1.txt

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Each researcher’s independent analysis of the lexical demarcation and metaphorical status of each word in the sample

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Eng2.R

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R code for Eng2

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Eng2.txt

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A second analysis of the same texts by the same three researchers, carried out after a comparison of responses in Eng 1

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