Rethinking "counterintuitive" results and analogical reasoning: a rejoinder to the critique of "erroneous regression".
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| Title: | Rethinking "counterintuitive" results and analogical reasoning: a rejoinder to the critique of "erroneous regression". |
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| Authors: | Mu, Guanglun Michael1 (AUTHOR) michael.mu@unisa.edu.au, Soong, Hannah1 (AUTHOR) hannah.soong@unisa.edu.au |
| Source: | Higher Education (00181560). Apr2026, Vol. 91 Issue 4, p1441-1448. 8p. |
| Subject Terms: | *Research methodology evaluation, *Academic discourse, *Analogy, *Foreign students, Statistical errors, Affordable housing, Reflexivity |
| Geographic Terms: | Australia |
| Abstract: | Since its online publication on 16 January 2025, Scapegoating international students for the rental crisis? Insights from large-scale evidence (2017–2024) in Australia has attracted significant attention and sparked widespread discussion. Among the responses is Kault's critique, Erroneous regression used to associate higher international student numbers with lower rents. As our publication continues to generate impact, Kault's critique is a welcome contribution, opening an intellectual avenue for scholarly debate, and providing an opportunity for us to reiterate viewpoints already made in the original publication and to offer necessary clarifications and further elaborations. In this response, we begin by recapitulating our study, followed by a summary of Kault's critique and the assumptions embedded in its allegations. We then address Kault's methodological challenges while drawing insights from established theses and existing studies to inform our rebuttal. We conclude by inviting the use of the reflexive tool of viewpoint, which enables critical and productive engagement with competing evidence and contrasting perspectives. [ABSTRACT FROM AUTHOR] |
| Copyright of Higher Education (00181560) is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Education Research Complete |
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