(Un) exceptional times: Compounding crises and local stakeholders in field work during COVID-19

Author:

Farfán-Méndez Cecilia1ORCID,Vizcarra Marcos2

Affiliation:

1. University of California San Diego, USA

2. Revista Espejo, Mexico

Abstract

From the positionality of a Mexican scholar in security studies who identifies as female and an investigative journalist born and working in Sinaloa, Mexico, this article builds on existing scholarship examining the positionality of local stakeholders who are integral to the production of knowledge in conflict settings. In early 2021, Mexico had the world's third-highest number of deaths caused by Covid-19. Additionally, close to 80,000 people were officially missing and 52,000 remains in state custody lacked identification. In this context, civil society groups raised concerns about the proper handling of bodies, fearing cremation prior to identification of the remains. The article highlights two phenomena as evidence of a reflexivity process followed by the authors: first, for mothers searching for their children, Covid-19 was an additional life-threatening risk (not the main health risk, as in the general population). Second, we consider how global pandemics produce compounding crises in contexts of chronic violence and vulnerability, while simultaneously bolstering advantages for scholars in the Global North. The article is a call to action for more ethical qualitative research methodologies within the emerging social science community working on illicit economies and extralegal actors.

Publisher

SAGE Publications

Reference52 articles.

1. Álvarez I (2021) Los “lugares peligrosos” de México: algunas consideraciones. In Blog sobre la política de seguridad. Available at: https://seguridad.nexos.com.mx/los-lugares-peligrosos-de-mexico-algunas-consideraciones/ (accessed 10 November 2021).

2. Dancing with danger: ethnographic safety, male bravado and gang research in Colombia

3. Real governance of the COVID-19 crisis in the Great Lakes region of Africa

4. Confronting Selection Bias: The Normative and Empirical Risks of Data Collection in Violent Contexts

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