The DOI matches its Crossref record; 66 of the 66 references it cites were found in a registry or an index.
Mobilizing Policy (In)Capacity to Fight COVID-19: Understanding Variations in State Responses
Open accessAbstract
The objective of this collection of essays is to gain insights into the different national-level state responses to COVID-19 around the world and the conditions that shaped them. The pandemic offers a natural experiment wherein the policy problem governments faced was the same but the responses they made were different, creating opportunities for comparison of both the kinds of policy tools being used and the factors that accounted for their choice. Accordingly, after surveying on-line databases of policy tools used in the pandemic and subjecting these to topic modelling to reveal the characteristics of a ‘standard’ national pandemic response, we discuss the similarities and differences found in specific responses. This is done with reference to the nature and level of policy capacity of respective governments, highlighting the critical roles played by (in)adequate preparation and lesson-drawing from past experiences with similar outbreaks or crises. Taken together the articles show how the national responses to the COVID-19 pandemic were shaped by the opportunity and capacity each government had to learn from previous pandemics and their capacity to operationalize and build political support for the standard portfolio of policy measures deployed to deal with the crisis. However, they also show how other factors such as the nature of national leadership, the organization of government and civil society, and blindspots towards the vulnerabilities of certain population segments also helped to shape policy responses to the pandemic.
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Cites
R: A Language and Environment for Statistical Computing
R Core Team (2025) · doi:10.32614/r.manuals · Cited by 352,181
Blei, D. M., Ng, A. Y., & Jordan, M. I. (2002) · Advances in Neural Information Processing Systems 14 · doi:10.7551/mitpress/1120.003.0082 · Cited by 12,223
An interactive web-based dashboard to track COVID-19 in real time
Dong, E., Du, H., & Gardner, L. (2020) · The Lancet Infectious Diseases · doi:10.1016/s1473-3099(20)30120-1 · Cited by 10,048
Introduction: epistemic communities and international policy coordination
Haas, P. M. (1992) · International Organization · doi:10.1017/s0020818300001442 · Cited by 7,584
Using social and behavioural science to support COVID-19 pandemic response
Bavel, J. J. V., Baicker, K., Boggio, P. S., Capraro, V., Cichocka, A., Cikara, M., Crockett, M. J., Crum, A. J., Douglas, K. M., Druckman, J. N., et al. (2020) · Nature Human Behaviour · doi:10.1038/s41562-020-0884-z · Cited by 4,964 · cited 1×
“…– in the form of social distancing, travel advisories and restrictions, school and university closures, and healthcare spending – were highly correlated not only with one another but also with the economic response; specifically, loans to businesses and monetary policy (Van Bavel et al., 2020).”
BackgroundEstimating the effects of non-pharmaceutical interventions on COVID-19 in Europe
Flaxman, S., Mishra, S., Gandy, A., Unwin, H. J. T., Mellan, T. A., Coupland, H., Whittaker, C., Zhu, H., Berah, T., Eaton, J. W., et al. (2020) · Nature · doi:10.1038/s41586-020-2405-7 · Cited by 3,350
Ferguson, N. M., Laydon, D. J., Nedjati-Gilani, G. L., Imai, N., Ainslie, K. E. C., Baguelin, M., Bhatia, S., Boonyasiri, A., Cucunubá, Z. M., Cuomo-Dannenburg, G., et al. (2020) · Spiral (Imperial College London) · doi:10.25561/77482 · Cited by 3,281
Creating public value: strategic management in government
(1996) · Choice Reviews Online · doi:10.5860/choice.33-4147 · Cited by 2,552
Creating public value : strategic management in government
Moore, M. H. (1995) · Medical Entomology and Zoology · Cited by 2,350
The Tools of government: a guide to the new governance
(2002) · Choice Reviews Online · doi:10.5860/choice.40-2422 · Cited by 1,827
Cited by
Learning from the COVID-19 crisis: an initial analysis of national responses
Boin, A., Lodge, M., & Luesink, M. (2020) · Policy Design and Practice · doi:10.1080/25741292.2020.1823670 · Cited by 192
Hogan, J., Howlett, M., & Murphy, M. (2022) · Policy and Society · doi:10.1093/polsoc/puab009 · Cited by 87
Self-citationKnill, C., & Steinebach, Y. (2022) · Policy and Society · doi:10.1093/polsoc/puab008 · Cited by 22
Ndlovu, S. (2023) · Sustainability · doi:10.3390/su15021420 · Cited by 11
Metadata
- Authors
- Capano, G., Howlett, M., Jarvis, D. S. L., Ramesh, M., & Goyal, N.
- Venue
- Policy and Society
- Publisher
- Oxford University Press (OUP)
- Published
- 2020-07-02
- Volume
- 39
- Issue
- 3
- Pages
- 285-308
- ISSN
- 1449-4035 (ISSN-L)
- 1839-3373
- OpenAlex
- W3038709602
- Cited by
- 579
- References
- 66
- FWCI
- 347.56
- Type
- journal article
- Language
- en
- Open access
- gold
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- Capano, G., Howlett, M., Jarvis, D. S. L., Ramesh, M., & Goyal, N. (2020). Mobilizing Policy (In)Capacity to Fight COVID-19: Understanding Variations in State Responses. Policy and Society. https://doi.org/10.1080/14494035.2020.1787628
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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