Understanding migrants in COVID-19 counting: Rethinking the data-(in)visibility nexus. (20th August 2021)
- Record Type:
- Journal Article
- Title:
- Understanding migrants in COVID-19 counting: Rethinking the data-(in)visibility nexus. (20th August 2021)
- Main Title:
- Understanding migrants in COVID-19 counting: Rethinking the data-(in)visibility nexus
- Authors:
- Pelizza, Annalisa
Milan, Stefania
Lausberg, Yoren - Abstract:
- Abstract: The COVID-19 pandemic confronts society with a dilemma between (in)visibility, security, and care. While invisibility might be sought by unregistered and undocumented people, being counted and thus visible during a pandemic is a precondition of existence and care. This article asks whether and how unregistered populations like undocumented migrants should be included in statistics and other "counting" exercises devised to track virus diffusion and its impact. In particular, the paper explores how such inclusion can be just, given that for unregistered people visibility is often associated with surveillance. It also reflects on how policymaking can act upon the relationship between data, visibility, and populations in pragmatic terms. Conversing with science and technology studies and critical data studies, the paper frames the dilemma between (in)visibility and care as an issue of sociotechnical nature and identifies four criteria linked to the sociotechnical characteristics of the data infrastructure enabling visibility. It surveys "counting" initiatives targeting unregistered and undocumented populations undertaken by European countries in the aftermath of the pandemic, and illustrates the medical, economic, and social consequences of invisibility. On the basis of our analysis, we outline four scenarios that articulate the visibility/invisibility binary in novel, nuanced terms, and identify in the "de facto inclusion" scenario the best option for both migrantsAbstract: The COVID-19 pandemic confronts society with a dilemma between (in)visibility, security, and care. While invisibility might be sought by unregistered and undocumented people, being counted and thus visible during a pandemic is a precondition of existence and care. This article asks whether and how unregistered populations like undocumented migrants should be included in statistics and other "counting" exercises devised to track virus diffusion and its impact. In particular, the paper explores how such inclusion can be just, given that for unregistered people visibility is often associated with surveillance. It also reflects on how policymaking can act upon the relationship between data, visibility, and populations in pragmatic terms. Conversing with science and technology studies and critical data studies, the paper frames the dilemma between (in)visibility and care as an issue of sociotechnical nature and identifies four criteria linked to the sociotechnical characteristics of the data infrastructure enabling visibility. It surveys "counting" initiatives targeting unregistered and undocumented populations undertaken by European countries in the aftermath of the pandemic, and illustrates the medical, economic, and social consequences of invisibility. On the basis of our analysis, we outline four scenarios that articulate the visibility/invisibility binary in novel, nuanced terms, and identify in the "de facto inclusion" scenario the best option for both migrants and the surrounding communities. Finally, we offer policy recommendations to avoid surveillance and overreach and promote instead a more just "de facto" civil inclusion of undocumented populations. … (more)
- Is Part Of:
- Data & policy. Volume 3(2021)
- Journal:
- Data & policy
- Issue:
- Volume 3(2021)
- Issue Display:
- Volume 3, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 3
- Issue:
- 2021
- Issue Sort Value:
- 2021-0003-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-08-20
- Subjects:
- COVID-19 -- critical data studies -- invisibility -- migrants -- science and technology studies
Policy sciences -- Periodicals
Policy sciences -- Statistical methods -- Periodicals
Policy sciences -- Data processing -- Periodicals
Decision making -- Data processing -- Periodicals
320.60727 - Journal URLs:
- https://www.cambridge.org/core/journals/data-and-policy ↗
- DOI:
- 10.1017/dap.2021.19 ↗
- Languages:
- English
- ISSNs:
- 2632-3249
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 18887.xml