Book contents
- Data-Intensive Investigations of English
- Studies in English Language
- Data-Intensive Investigations of English
- Copyright page
- Contents
- Figures
- Tables
- Contributors
- Acknowledgments
- Chapter 1 Data-Intensive Approaches to English Linguistics
- Chapter 2 What Big Data Tells Us about American English Phonetics
- Chapter 3 Do You Reckon?
- Chapter 4 ‘Scots for the Masses’?
- Chapter 5 Combining Collocation Measures and Distributional Semantics to Detect Idioms
- Chapter 6 Using Data-Intensive Methods for Unlocking Expressiveness in Word Formation
- Chapter 7 Modals of Future Time Reference across Native and Non-native Englishes
- Chapter 8 Bayesian Multivariate Analysis of Complement Selection
- Chapter 9 Statistical Modelling of Syntactic Complexity of English Academic Texts Using Ensemble Machine Learning
- Chapter 10 Implications of the Replication Crisis
- Index
- References
Chapter 10 - Implications of the Replication Crisis
Some Suggestions to Improve Reproducibility and Transparency in Data-Intensive Corpus Linguistics
Published online by Cambridge University Press: 03 December 2025
Book contents
- Data-Intensive Investigations of English
- Studies in English Language
- Data-Intensive Investigations of English
- Copyright page
- Contents
- Figures
- Tables
- Contributors
- Acknowledgments
- Chapter 1 Data-Intensive Approaches to English Linguistics
- Chapter 2 What Big Data Tells Us about American English Phonetics
- Chapter 3 Do You Reckon?
- Chapter 4 ‘Scots for the Masses’?
- Chapter 5 Combining Collocation Measures and Distributional Semantics to Detect Idioms
- Chapter 6 Using Data-Intensive Methods for Unlocking Expressiveness in Word Formation
- Chapter 7 Modals of Future Time Reference across Native and Non-native Englishes
- Chapter 8 Bayesian Multivariate Analysis of Complement Selection
- Chapter 9 Statistical Modelling of Syntactic Complexity of English Academic Texts Using Ensemble Machine Learning
- Chapter 10 Implications of the Replication Crisis
- Index
- References
Summary
This chapter examines the implications of the Replication Crisis for corpus linguistics and humanities researchers working with language data. It highlights common issues and workflows in corpus linguistics that hinder reproducibility and offers guidance on improving data management, sharing practices and transparency of analyses. The discussion addresses several key issues prevalent in the field, including a lack of training on enhancing reproducibility, disorganized data management, analysis procedures that impede replication, and convoluted workflows compounded by limited resources. These challenges are particularly pronounced in qualitative and interpretive work, where specific attention is required, but also concern any type of data-intensive analysis. To address the issues, the chapter provides pointers to resources, practices, and tools that enhance data management and transparency of analyses in corpus linguistics, and it shows how these resources can be put into practice using the illustrative example of a study on adjective amplification in selected varieties of Asian Englishes. By adopting improved methods, researchers adhere to best practices and thereby enhance reproducibility, transparency, and the overall research quality in corpus linguistics.
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- Type
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- Information
- Data-Intensive Investigations of English , pp. 258 - 286Publisher: Cambridge University PressPrint publication year: 2025
References
Anderson, Christopher J., Bahnik, Štěpán, Barnett-Cowan, Michael, Bosco, Frank A., Chandler, Jesse, Chartier, Christopher R. … Zuni, Kellylynn (2016). ‘Response to comment on “Estimating the reproducibility of psychological science”’. Science, 351(6277), 1037. https://doi.org/10.1126/science.aad9163.CrossRefGoogle ScholarPubMed
Andreassen, Helene N., Conzett, Philipp, Høydalsvik, Stein, Longva, Leif and Obiajulu, Odu (2017). ‘TROLLing: Scope and operation of an open repository for linguistic datasets’, poster presented at the Linguistic Society of America symposium in the poster session on Data Citation and Attribution in Linguistics, 5–9 January 2017, Austin, TX. https://scholarspace.manoa.hawaii.edu/items/3ea48279-7913-4e7b-81e0-d4a78fcfaf0d.Google Scholar
Anthony, Laurence (2020). ‘Programming for corpus linguistics’, in Paquot, Magali and Gries, Stefan Th. (eds.), A Practical Handbook of Corpus Linguistics. Berlin: Springer, pp. 181–207.CrossRefGoogle Scholar
Arppe, Antti, Gilquin, Gaëtanelle, Glynn, Dylan, Hilpert, Martin and Zeschel, Arne (2010). ‘Cognitive corpus linguistics: Five points of debate on current theory and methodology’. Corpora, 5(1), 1–27. https://doi.org/10.3366/cor.2010.0001.CrossRefGoogle Scholar
Baayen, R. Harald (2008). Analyzing Linguistic Data: A Practical Introduction to Statistics Using R. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Barwick, Linda and Thieberger, Nick (2012). ‘Keeping records of language diversity in Melanesia: The Pacific and Regional Archive for Digital Sources in Endangered Cultures (PARADISEC)’, in Evans, Nicholas and Klamer, Marian (eds.), Melanesian Languages on the Edge of Asia: Challenges for the 21st Century. Manoa: University of Hawai‘i Press, pp. 239–253. https://scholarspace.manoa.hawaii.edu/server/api/core/bitstreams/55073d3c-5f8e-4545-b277-c85e05acf207/content.Google Scholar
Bednarek, Monika, Schweinberger, Martin and Lee, Kelvin (2024). ‘Corpus-based discourse analysis: From meta-reflection to accountability’. Corpus Linguistics and Linguistic Theory (Special Issue). https://doi.org/10.1515/cllt-2023-0104.CrossRefGoogle Scholar
Bell, Peter and Beer, Brent (2018). Introducing GitHub: A Non-technical Guide. Sebastopol, CA: O’Reilly.Google Scholar
Berez-Kroeker, Andrea L., Lauren, Gawne, Kung, Susan S., Kelly, Barbara F., Tyler, Heston, Gary, Holton, … Woodbury, Anthony (2018). ‘Reproducible research in linguistics: A position statement on data citation and attribution in our field’. Linguistics, 56(1), 1–18. https://doi.org/10.1515/ling-2017-0032.CrossRefGoogle Scholar
Berez-Kroeker, Andrea L., McDonnell, Bradley, Koller, Eve and Collister, Lauren B. (eds.) (2022a). The Open Handbook of Linguistic Data Management. Cambridge, MA: The MIT Press.CrossRefGoogle Scholar
Berez-Kroeker, Andrea L., McDonnell, Bradley, Collister, Lauren B. and Koller, Eve (2022b). ‘Chapter 1: Data, data management, and reproducible research in linguistics: On the need for The Open Handbook of Linguistic Data Management’, in Berez-Kroeker, Andrea L., McDonnell, Bradley, Koller, Eve and Collister, Lauren B. (eds.), The Open Handbook of Linguistic Data Management. Cambridge, MA: MIT Press, pp. 3–8.CrossRefGoogle Scholar
Bergman, Ofer, Whittaker, Steve, Sanderson, Mark, Nachmias, Rafi and Ramamoorthy, Anand (2010). ‘The effect of folder structure on personal file navigation’. Journal of the American Society for Information Science and Technology, 61(12), 2426–2441. https://doi.org/10.1002/asi.21415.CrossRefGoogle Scholar
Birkbeck, Gail, Nagle, Tadhg and Sammon, David (2022). ‘Challenges in research data management practices: A literature analysis’. Journal of Decision Systems, 31(sup1), 153–167. https://doi.org/10.1080/12460125.2022.2074653.CrossRefGoogle Scholar
Blischak, John D., Davenport, Emily R. and Wilson, Greg (2016). ‘A quick introduction to version control with Git and GitHub’. PLoS Computational Biology, 12(1), e1004668. https://doi.org/10.1371/journal.pcbi.1004668.CrossRefGoogle ScholarPubMed
Boas, Hans C. (2006). ‘From the field to the web: Implementing best-practice recommendations in documentary linguistics’. Language Resources and Evaluation, 40, 153–174. https://doi.org/0.1007/s10579-006-9012-6.CrossRefGoogle Scholar
Bochynska, Agata, Liam, Keeble, Caitlin, Halfacre, Casillas, Joseph V., Champagne, Irys-Amélie, Kaidi, Chen, … Roettger, Timo B. (2023). ‘Reproducible research practices and transparency across linguistics’. Glossa Psycholinguistics, 2(1), 18. https://doi.org/10.5070/G6011239.CrossRefGoogle Scholar
Bolibaugh, Cylcia and Marsden, Emma (2021). ‘Reproducibility and research integrity in applied linguistics’. MetaArXiv, 9 December 2021. https://doi.org/10.31222/osf.io/3ucbv.CrossRefGoogle Scholar
Braga, Pedro H. P., Hébert, Katherine, Hudgins, Emma J., Scott, Eric R., Edwards, Brandon P., Sánchez-Reyes, Luna L. S., … Crystal-Ornelas, Robert (2023). ‘Not just for programmers: How GitHub can accelerate collaborative and reproducible research in ecology and evolution’. Manubot. https://sortee-github-hackathon.github.io/manuscript/v/latest/.Google Scholar
Collister, Lauren B. (2022). ‘Chapter 9: Copyright and sharing linguistic data’, in Berez-Kroeker, Andrea L., McDonnell, Bradley, Koller, Eve and Collister, Lauren B. (eds.), The Open Handbook of Linguistic Data Management. Cambridge, MA: MIT Press, pp. 117–128. https://doi.org/10.7551/mitpress/12200.003.0013.CrossRefGoogle Scholar
Coplien, Jim and Harrison, Neil (2004). Organizational Patterns of Agile Software Development. Englewood Cliffs, NJ: Prentice Hall.Google Scholar
Desagulier, Guillaume (2017). Corpus Linguistics and Statistics with R. Cham: Springer International.CrossRefGoogle Scholar
Diener, Edward and Biswas-Diener, Robert (2019). ‘The Replication Crisis in psychology’, in Biswas-Diener, Robert and Diener, Edward (eds.), Noba Textbook Series: Psychology. Champaign, IL: DEF Publishers. https://nobaproject.com/modules/the-replication-crisis-in-psychology.Google Scholar
Dillon, Cy (2015). ‘The Center for Open Science cultivates openness, integrity, and reproducibility’. College & Undergraduate Libraries, 22(2), 224–228. https://doi.org/10.1080/10691316.2015.1035182.CrossRefGoogle Scholar
Flanagan, Joseph (2017). ‘Reproducible research: Strategies, tools, and workflows’, in Hiltunen, Turo, McVeigh, Joe and Säily, Tanja (eds.), Studies in Variation, Contacts and Change in English 19: Big and Rich Data in English Corpus Linguistics: Methods and Explorations. Helsinki: VARIENG e-series. www.helsinki.fi/varieng/series/volumes/19/flanagan/.Google Scholar
Foster, Erin D. and Deardorff, Ariel (2017). ‘Open science framework (OSF)’. Journal of the Medical Library Association: JMLA, 105(2), 203. https://doi.org/10.5195/jmla.2017.88.CrossRefGoogle Scholar
Gawne, Lauren and Styles, Suzy (2022). ‘Chapter 2: Situating linguistics in the Social Science Data Movement’, in Berez-Kroeker, Andrea L., McDonnell, Bradley, Koller, Eve and Collister, Lauren B. (eds.), The Open Handbook of Linguistic Data Management. Cambridge, MA: MIT Press, pp. 9–26. https://doi.org/10.7551/mitpress/12200.003.0006.CrossRefGoogle Scholar
Gewin, Virginia (2016). ‘Data sharing: An open mind on open data’. Nature, 529(7584), 117–119. https://doi.org/10.1038/nj7584-117a.CrossRefGoogle ScholarPubMed
Goodman, Steven N., Fanelli, Daniele and Ioannidis, John P. (2016). ‘What does research reproducibility mean?’ Science Translational Medicine, 8(341), 341ps12. https://doi.org/10.1126/scitranslmed.aaf5027.CrossRefGoogle ScholarPubMed
Grabus, Sam and Greenberg, Jane (2019). ‘The landscape of rights and licensing initiatives for data sharing’. Data Science Journal, 18, 29–29. https://doi.org/10.5334/dsj-2019-029.CrossRefGoogle Scholar
Greenbaum, Sidney (1991). ‘ICE: The International Corpus of English’. English Today, 7(4), 3–7. https://doi.org/10.1017/S0266078400005836.CrossRefGoogle Scholar
Gries, Stefan Th. (2016). Quantitative Corpus Linguistics with R: A Practical Introduction. New York: Routledge.CrossRefGoogle Scholar
Gries, Stefan Th. (2021). Statistics for Linguistics with R. Berlin: De Gruyter Mouton.CrossRefGoogle Scholar
Gries, Stefan Th. (2025). ‘Closing remarks and outlook’.International Journal of Corpus Linguistics ( Special Issue on Reproducibility, Replication and Robustness in Corpus Linguistics). https://doi.org/10.1075/ijcl.24120.gri.CrossRefGoogle Scholar
Grieve, Jack (2021). ‘Observation, experimentation, and replication in linguistics’. Linguistics, 59(5), 1343–1356. https://doi.org/10.1515/ling-2021-0094.CrossRefGoogle Scholar
Grüning, Björn, Chilton, John, Köster, Johannes, Dale, Ryan, Soranzo, Nicola, van den Beek, Marius, … Taylor, James (2018). ‘Practical computational reproducibility in the Life Sciences’. Cell Systems, 6(6), 631–635. https://doi.org/10.1016/j.cels.2018.03.014.CrossRefGoogle ScholarPubMed
Gundersen, Odd E. (2021). ‘The fundamental principles of reproducibility’. Philosophical Transactions of the Royal Society A, 379, 20200210. https://doi.org/10.1098/rsta.2020.0210.CrossRefGoogle Scholar
Hammond, Michael (2020). Python for Linguists. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Heron, Michael, Hanson, Vicki L. and Ricketts, Ian (2013). ‘Open source and accessibility: advantages and limitations’. Journal of Interaction Science, 1, 1–10. https://doi.org/10.1186/2194-0827-1-2.CrossRefGoogle Scholar
Hethey, Jonathan M. (2013). GitLab Repository Management. Birmingham: Packt Publishing.Google Scholar
Holton, Gary, Leonard, Wesley Y. and Pulsifer, Peter L. (2022). ‘Indigenous peoples, ethics, and linguistic data’, in Berez-Kroeker, Andrea L., McDonnell, Bradley, Koller, Eve and Collister, Lauren B. (eds.), The Open Handbook of Linguistic Data Management. Cambridge, MA: MIT Press, pp. 49–60. https://doi.org/10.7551/mitpress/12200.003.0008.CrossRefGoogle Scholar
Huberman, A. Michael and Miles, Matthew B. (1994). ‘Data management and analysis methods’, in Denzin, Norman K. and Lincoln, Yvonna S. (eds.), Handbook of Qualitative Research. Thousand Oaks, CA: Sage, pp. 428–444.Google Scholar
Ioannidis, John P. A. (2005). ‘Why most published research findings are false’. PLoS Medicine, 2(8), e124. https://doi.org/10.1371/journal.pmed.0020124.CrossRefGoogle ScholarPubMed
Isbell, Daniel R., Brown, Dan, Chen, Meishan, Derrick, Deirdre J., Ghanem, Romy, Arvizu, María N. G., … Plonsky, Luke (2022). ‘Misconduct and questionable research practices: The ethics of quantitative data handling and reporting in applied linguistics’. The Modern Language Journal, 106(1), 172–195. https://doi.org/10.1111/modl.12760.CrossRefGoogle Scholar
Jacobsen, Annika, de Miranda Azevedo, Ricardo, Juty, Nick, Batista, Dominique, Coles, Simon, Cornet, Ronald, Courtot, Mélanie, … Mons, Barend (2020). ‘FAIR principles: Interpretations and implementation considerations’. Data Intelligence, 2(1–2), 10–29. https://doi.org/10.1162/dint_r_00024.CrossRefGoogle Scholar
Jahnke, Lori M. and Asher, Andrew (2012). ‘The problem of data: Data management and curation practices among university researchers’. The Problem of Data, 3–31. www.clir.org/pubs/reports/pub154/problem-of-data.Google Scholar
Janda, Laura A. (2017). ‘The quantitative turn’, in Dancygier, Barbara (ed.), The Cambridge Handbook of Cognitive Linguistics. Cambridge: Cambridge University Press, pp. 498–514.CrossRefGoogle Scholar
Klein, Richard A., Ratliff, Kate A., Vianello, Michelangelo, Adams, Reginal B. Jr., Bahnik, Stĕpán, Bernstein, Michael J., … Nosek, Brian A. (2014). ‘Data from investigating variation in replicability: A “Many Labs” replication project’. Journal of Open Psychology Data, 2(1), 142–152. https://doi.org/10.5334/jopd.ad.Google Scholar
Kortmann, Bernd (2021). ‘Reflecting on the quantitative turn in linguistics’. Linguistics, 59(5), 1207–1226. https://doi.org/10.1515/ling-2019-0046.CrossRefGoogle Scholar
Krauwer, Steven and Hinrichs, Erhard (2014). ‘The CLARIN research infrastructure: Resources and tools for e-humanities scholars’. In Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC-2014). European Language Resources Association (ELRA), pp. 1525–1531.Google Scholar
Lakens, Daniel (2014). ‘The reproducibility project: A model of large-scale collaboration for empirical research on reproducibility’, in Stodden, Viktoria, Leisch, Friedrich and Peng, Roger D. (eds.), Implementing Reproducible Research. New York: Taylor and Francis, pp. 299–324.Google Scholar
Larsson, Tove, Egbert, Jesse and Biber, Douglas (2022). ‘On the status of statistical reporting versus linguistic description in corpus linguistics: A ten-year perspective’. Corpora, 17(1), 137–157. https://doi.org/10.3366/cor.2022.0238.CrossRefGoogle Scholar
Levshina, Natalia (2015). How to Do Linguistics with R: Data Exploration and Statistical Analysis. Amsterdam: John Benjamins.CrossRefGoogle Scholar
Mattern, Eleanor (2022). ‘The linguistic data life cycle, sustainability of data, and principles of solid data management’, in Berez-Kroeker, Andrea L., McDonnell, Bradley, Koller, Eve and Collister, Lauren B. (eds.), The Open Handbook of Linguistic Data Management. Cambridge, MA: The MIT Press. https://doi.org/10.7551/mitpress/12200.003.0009.Google Scholar
McMurry, Julie A., Juty, Nick, Blomberg, Niklas, Burdett, Tony, Conlin, Tom, Conte, Nathalie, … Parkinson, Helen (2017). ‘Identifiers for the 21st century: How to design, provision, and reuse persistent identifiers to maximize utility and impact of life science data’. PLoS Biology, 15(6), e2001414. https://doi.org/10.1371/journal.pbio.2001414.CrossRefGoogle ScholarPubMed
McRae, Mike (2018). ‘Science’s “Replication Crisis” has reached even the most respectable journals, report shows’. ScienceAlert. www.sciencealert.com/replication-results-reproducibility-crisis-science-nature-journals.Google Scholar
Mertzen, Daniela, Lago, Sol and Shravan, Vasishth (2021). ‘The benefits of preregistration for hypothesis-driven bilingualism research’. Bilingualism: Language and Cognition, 24(5), 807–812. https://doi.org/10.1017/S1366728921000031.CrossRefGoogle Scholar
Miotto, Amanda Toohey, Julie and Weaver, Belinda (2024). Reproducible-Research-Things. GitHub. https://guereslib.github.io/Reproducible-Research-Things/.Google Scholar
Moonesinghe, Ramal, Khoury, Muin J. and Janssens, A. Cecile J. W. (2007). ‘Most published research findings are false – but a little replication goes a long way’. PLoS Medicine, 4(2), e28. https://doi.org/10.1371/journal.pmed.0040028.CrossRefGoogle ScholarPubMed
Moravcsik, Andrew (2019). ‘Transparency in qualitative research’. SAGE Research Methods Foundations. www.princeton.edu/~amoravcs/library/TransparencyinQualitativeResearch.pdf. https://doi.org/10.4135/9781526421036.CrossRefGoogle Scholar
Munafò, Marcus R. and Davey Smith, George (2018). ‘Robust research needs many lines of evidence’. Nature, 553(7689), 399–401. https://doi.org/10.1038/d41586-018-01023-3.CrossRefGoogle ScholarPubMed
Nosek, Brian (2022). ‘Continued growth in OSF usage: Catalyzing change in open practices’. Center for Open Science (COS). www.cos.io/blog/continued-growth-in-osf-usage.Google Scholar
Nosek, Brian A. and Errington, Timothy M. (2020). ‘What is replication?’ PLoS Biology, 18(3), e3000691. https://doi.org/10.1371/journal.pbio.3000691.CrossRefGoogle ScholarPubMed
Open Science Collaboration (2015). ‘Estimating the reproducibility of psychological science’. Science, 349(6251), aac4716. https://doi.org/10.1126/science.aac4716.CrossRefGoogle Scholar
Peer, Limor, Arguillas, Florio, Honeyman, Tom, Miljković, Nadica, Peters-von Gehlen, Karsten and CURE-FAIR Subgroup 3 (2021). Challenges of Curating for Reproducible and FAIR Research Output (V2.0 [changes from V1.1]). RDA CURE-FAIR Working Group, Subgroup 3, on CURE-FAIR Challenges, 12 April 2021.Google Scholar
Posit Team (2024). RStudio: Integrated Development Environment for R: Posit Software. Boston: Public Benefit Corporation. www.posit.co.Google Scholar
R Core Team (2023). R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. www.R-project.org.Google Scholar
Roettger, Timo B. (2021). ‘Preregistration in experimental linguistics: Applications, challenges, and limitations’. Linguistics, 59(5), 1227–1249. https://doi.org/10.1515/ling-2019-0048.CrossRefGoogle Scholar
Ruggiero, Paul and Heckathorn, Matthew A. (2012). ‘Data Backup Options’: US-CERT United States Computer Emergency Readiness Team. Austria: Carnegie Mellon University.Google Scholar
Schweinberger, Martin (2024). ‘A corpus‐based analysis of adjective amplification in Hong Kong, Indian and Philippine English’. World Englishes, 1–18. https://doi.org/10.1111/weng.12640.CrossRefGoogle Scholar
Schweinberger, Martin and Haugh, Michael (2025a). ‘Reproducibility and transparency in interpretive corpus pragmatics’. International Journal of Corpus Linguistics (Special Issue: Reproducibility, Replication and Robustness in Corpus Linguistics). https://doi.org/10.1075/ijcl.23033.sch.CrossRefGoogle Scholar
Schweinberger, Martin and Haugh, Michael (2025b). ‘Reproducibility, replicability, and robustness in corpus linguistics: An introduction’. International Journal of Corpus Linguistics (Special Issue: Reproducibility, Replication and Robustness in Corpus Linguistics). www.jbe-platform.com/content/journals/10.1075/ijcl.25081.sch.CrossRefGoogle Scholar
Sefton, Peter, Sacal Bonequi, Moises, Musgrave, Simon and Fewster, Jenny (2023). ‘A CARE-and FAIR-ready distributed access control system for human-created data’, in Proceedings of the Second International Workshop on Digital Language Archives: LangArc 2023. Denton, TX: University of North Texas Press, pp. 23–27.Google Scholar
Simmons, Joseph P., Nelson, Leif D. and Simonsohn, Uri (2021). ‘Pre-registration: Why and how’. Journal of Consumer Psychology, 31(1), 151–162. https://doi.org/10.1002/jcpy.1208.CrossRefGoogle Scholar
Simons, Daniel J. (2014). ‘The value of direct replication’. Perspectives on Psychological Science, 9(1), 76–80. https://doi.org/10.1177/1745691613514755.CrossRefGoogle ScholarPubMed
Sönning, Lukas and Werner, Valentin (2021). ‘The replication crisis, scientific revolutions, and linguistics’. Linguistics (Special Issue: The Replication Crisis: Implications for Linguistics), 59(5), 1179–1206. https://doi.org/10.1515/ling-2019-0045.Google Scholar
Wallach, Joshua D., Boyack, Kevin W. and Ioannidis, John P. (2018). ‘Reproducible research practices, transparency, and open access data in the biomedical literature, 2015–2017’. PLoS Biology, 16(11), e2006930. https://doi.org/10.1371/journal.pbio.2006930.CrossRefGoogle ScholarPubMed
Winter, Bodo (2019). Statistics for Linguists: An Introduction Using R. New York: Routledge.CrossRefGoogle Scholar
Wood, Margaret, Larsson, Tove, Plonsky, Luke, Sterling, Scott, Kytö, Merja and Yaw, Katherine (2024). Addressing Questionable Research Practices in Applied Linguistics: A Practical Guide. Applied Linguistics Press.Google Scholar
Yong, Ed (2018). ‘Psychology’s replication crisis is running out of excuses’. The Atlantic. www.theatlantic.com/science/archive/2018/11/psychologys-replication-crisis-real/576223/.Google Scholar
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