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Approachable modeling and smart methods: a new methods field of study

Schimpf, Corey; Castellani, Brian

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Corey Schimpf


Advances in the integration of smart technology with interdisciplinary methods has created a new genre, approachable modeling and smart methods – AM-Smart for short. AM-Smart platforms address a major challenge for applied and public sector analysts, educators and those trained in traditional methods: accessing the latest advances in interdisciplinary (particularly computational) methods. AM-Smart platforms do so through nine design features. They are (1) bespoke tools that (2) involve a single or small network of interrelated (mostly computational) methods. They also (3) embed distributed expertise, (4) scaffold methods use, (5) provide rapid and formative feedback, (6) leverage visual reasoning, (7) enable productive failure, and (8) promote user-driven inquiry; all while (9) counting as rigorous and reliable tools. Examples include R-shiny programmes, computational modeling and statistical apps, public-sector data management platforms, data visualisation tools, and smart phone apps. Critical reflection on AM-Smart platforms, however, reveals considerable unevenness in these design features, which hamper their effectiveness. A rigorous research agenda is vital. After situating the AM-Smart genre in its historical context and introducing a short list of platforms, we review the above nine features, including a use-case on how AM-Smart platforms ideally work. We end with a research agenda for advancing the AM-Smart genre.


Schimpf, C., & Castellani, B. (2022). Approachable modeling and smart methods: a new methods field of study. International Journal of Social Research Methodology,

Journal Article Type Article
Acceptance Date Aug 5, 2022
Online Publication Date Aug 17, 2022
Publication Date Aug 17, 2022
Deposit Date Sep 21, 2022
Publicly Available Date Sep 22, 2022
Journal International Journal of Social Research Methodology
Print ISSN 1364-5579
Electronic ISSN 1464-5300
Publisher Taylor and Francis Group
Peer Reviewed Peer Reviewed
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Published Journal Article (Advance online version) (1.8 Mb)

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Copyright Statement
Advance online version This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (, which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.

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