The DOI matches its Crossref record.
Real Social Science: Applied Phronesis
Abstract
Real Social Science presents a new, hands-on approach to social inquiry. The theoretical and methodological ideas behind the book, inspired by Aristotelian phronesis, represent an original perspective within the social sciences, and this volume gives readers for the first time a set of studies exemplifying what applied phronesis looks like in practice. The reflexive analysis of values and power gives new meaning to the impact of research on policy and practice. Real Social Science is a major step forward in a novel and thriving field of research. This book will benefit scholars, researchers and students who want to make a difference in practice, not just in the academy. Its message will make it essential reading for students and academics across the social sciences.
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Citations
Cited by
mHealth for Maternal Mental Health: Everyday Wisdom in Ethical Design
Barry, M., Doherty, K., Marcano Belisario, J., Car, J., Morrison, C., & Doherty, G. (2017) · Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3025453.3025918 · Cited by 57
Metadata
- Venue
- Cambridge University Press eBooks
- Publisher
- Cambridge University Press
- Published
- 2012-04-19
- OpenAlex
- W1533633778
- Cited by
- 357
- References
- 0
- FWCI
- 14.63
- Type
- book
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
