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Generalization And Induction: Misconceptions, Clarifications And A Classification Of Induction, Eric W. K. Tsang, John N. Williams
Generalization And Induction: Misconceptions, Clarifications And A Classification Of Induction, Eric W. K. Tsang, John N. Williams
John N. WILLIAMS
In “Generalizing Generalizability in Information Systems Research,” Lee and Baskerville (2003) try to clarify generalization and classify it into four types. Unfortunately, their account is problematic. We propose repairs. Central among these is our balance-of-evidence argument that we should adopt the view that Hume’s problem of induction has a solution, even if we do not know what it is. We build upon this by proposing an alternative classification of induction. There are five types of generalization: (1) theoretical, (2) within-population, (3) cross-population, (4) contextual, and (5) temporal, with theoretical generalization being across the empirical and theoretical levels and the rest …
Generalization And Induction: More Misconceptions And Clarifications, Eric W. K. Tsang, John N. Williams
Generalization And Induction: More Misconceptions And Clarifications, Eric W. K. Tsang, John N. Williams
John N. WILLIAMS
In ‘Generalization and Induction: Misconceptions, Clarifications, and a Classification of Induction’, we comment on Lee and Baskerville’s (2003) paper ‘Generalizing Generalizability in Information Systems Research’, which attempts to clarify the concept of generalization and classify it into four types. Our commentary discusses the misconceptions in their paper and proposes an alternative classification of induction. Their response ‘Conceptualizing Generalizability: New Contributions and a Reply’ perpetuates their misconceptions and create new ones. The purpose of this rejoinder is to highlight the major problems both in their original paper and in their reply and to provide further clarifications. Lee and Baskerville’s so-called ‘new …