Corpus linguistics will benefit from greater adoption of pre-registration: A novice-friendly split-corpus approach to pre-registration

In this brief article, I contend that the field of corpus linguistics stands to gain significantly from an increased adoption of pre-registration. Pre-registration serves to constrain the almost infinite degree of analytic freedom inherent in corpus analysis, thereby enhancing the transparency, reliability, and potential impact of corpus research. While pre-registration is increasingly popular in fields such as psychology and medicine, its uptake in corpus linguistics remains notably limited. To facilitate the transition toward pre-registration, I describe a straightforward split-corpus approach, ideally suited for corpus linguists new to pre-registration and for both hypothesis-testing and exploratory research. This method involves dividing a corpus into an exploratory set (20–40 % of the corpus) and a confirmatory set (the remaining 60–80 %). The exploratory set allows researchers to freely generate hypotheses and develop analysis plans, while the confirmatory set is then used for a more structured and objective analysis according to the pre-specified protocols. By employing this approach, corpus linguists can effectively balance exploratory flexibility with the rigour of confirmatory analysis, boosting the reliability of corpus findings. An increased uptake of pre-registration may not only bolster recognition of corpus linguistics as a robust empirical field, but it may also encourage a stronger emphasis on the building of cumulative knowledge.

Authors

Institutions

Publication Details

Journal
Applied Corpus Linguistics
Published
2024-10-11
DOI
https://doi.org/10.1016/j.acorp.2024.100111
Citations
2
Primary Topic
Natural Language Processing Techniques
Type
article
Field-Weighted Citation Impact
0.69
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Corpus linguistics will benefit from greater adoption of pre-registration: A novice-friendly split-corpus approach to pre-registration

Matthew HC Mak
2 citations
Applied Corpus Linguistics
Natural Language Processing Techniques
0.69
article

Corpus linguistics will benefit from greater adoption of pre-registration: A novice-friendly split-corpus approach to pre-registration

Matthew HC Mak
article en
2 citations

Abstract

In this brief article, I contend that the field of corpus linguistics stands to gain significantly from an increased adoption of pre-registration. Pre-registration serves to constrain the almost infinite degree of analytic freedom inherent in corpus analysis, thereby enhancing the transparency, reliability, and potential impact of corpus research. While pre-registration is increasingly popular in fields such as psychology and medicine, its uptake in corpus linguistics remains notably limited. To facilitate the transition toward pre-registration, I describe a straightforward split-corpus approach, ideally suited for corpus linguists new to pre-registration and for both hypothesis-testing and exploratory research. This method involves dividing a corpus into an exploratory set (20–40 % of the corpus) and a confirmatory set (the remaining 60–80 %). The exploratory set allows researchers to freely generate hypotheses and develop analysis plans, while the confirmatory set is then used for a more structured and objective analysis according to the pre-specified protocols. By employing this approach, corpus linguists can effectively balance exploratory flexibility with the rigour of confirmatory analysis, boosting the reliability of corpus findings. An increased uptake of pre-registration may not only bolster recognition of corpus linguistics as a robust empirical field, but it may also encourage a stronger emphasis on the building of cumulative knowledge.

Applied Corpus LinguisticsVol. 4(3)
University of Warwick (GB)
Quality Education
Openalex Percentile: Top 24%
Natural Language Processing Techniques
0.69
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.