dc.contributor.author |
Mabugu, Ramos Emmanuel
|
|
dc.contributor.author |
Maisonnave, Helene
|
|
dc.contributor.author |
Henseler, Martin
|
|
dc.contributor.author |
Chitiga-Mabugu, Margaret
|
|
dc.contributor.author |
Makochekanwa, Albert
|
|
dc.date.accessioned |
2024-04-25T06:13:42Z |
|
dc.date.available |
2024-04-25T06:13:42Z |
|
dc.date.issued |
2023-10 |
|
dc.description.abstract |
This article presents lessons on transcendence, from research on the socioeconomic impacts of the Covid-19 pandemic to policy, using experiences from Zimbabwe. The case study parallels literature on knowledge translation that suggests that the challenge of evidence-informed policy is more a problem of evidence production than evidence translation. The positioning, influence, and leverage of the research team was predominantly built on a platform of personal relationship legacies, academic legitimacy, and networks. The data and model co-produced with state actors could influence policy decisions and behaviours because they were designed with and for policymakers to assist with policy decisions. The results had direct implications for Covid-19 response measures, informing policymakers on what the impact on different groups is likely to be and indicating what policy measures could do to address impacts. Knowledge co‑production also proved pivotal in reducing some of the concerns around the limitations of risk‑based modelling in a crisis. |
en_US |
dc.description.department |
School of Public Management and Administration (SPMA) |
en_US |
dc.description.librarian |
hj2024 |
en_US |
dc.description.sdg |
SDG-17:Partnerships for the goals |
en_US |
dc.description.sponsorship |
The Partnership for Economic Policy (PEP), with funding from the Government of Canada through the IDRC. |
en_US |
dc.description.uri |
https://bulletin.ids.ac.uk/index.php/index |
en_US |
dc.identifier.citation |
Mabugu, R.E., Maisonnave, H., Henseler, M. et al. 2023, 'Co-modelling for relief and recovery from the Covid-19 crisis in Zimbabwe', IDS Bulletin, vol. 54, no. 2, pp. 41-58, doi : 10.19088/1968-2023.131. |
en_US |
dc.identifier.issn |
0265-5012 (print) |
|
dc.identifier.issn |
1759-5436 (online) |
|
dc.identifier.other |
10.19088/1968-2023.131 |
|
dc.identifier.uri |
http://hdl.handle.net/2263/95754 |
|
dc.language.iso |
en |
en_US |
dc.publisher |
Institute of Development Studies |
en_US |
dc.rights |
© 2023 The Authors. IDS Bulletin © Institute of Development Studies. This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 International licence (CC BY). |
en_US |
dc.subject |
Collaborative modelling |
en_US |
dc.subject |
Bilateral learning |
en_US |
dc.subject |
Risk-based modelling concerns |
en_US |
dc.subject |
Knowledge translation |
en_US |
dc.subject |
Evidence-informed policy |
en_US |
dc.subject |
COVID-19 pandemic |
en_US |
dc.subject |
Coronavirus disease 2019 (COVID-19) |
en_US |
dc.subject |
Zimbabwe |
en_US |
dc.subject |
SDG-17: Partnerships for the goals |
en_US |
dc.title |
Co-modelling for relief and recovery from the Covid-19 crisis in Zimbabwe |
en_US |
dc.type |
Article |
en_US |