The masking and making of fieldworkers and data in postcolonial Global Health research contexts
The masking and making of fieldworkers and data in postcolonial Global Health research contexts
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DOI：
10.1080/09581596.2019.1609650
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发表时间：
2019-08-08
影响因子：
2.8
通讯作者：
Gerrets, Rene
中科院分区：
文献类型：
--
作者：
Kingori, Patricia;Gerrets, Rene
本文重点讨论了后殖民背景下的现场工作人员（当地数据收集者）在全球健康研究中的作用和贡献。它是由两个不同的东非生物医学研究机构进行的两项独立的人种学研究提供的信息。它讨论了田野工作人员“低技能”和“本地”的共同特征如何使他们在两个重要方面对研究机构有吸引力：作为社区嵌入的数据收集者，从而促进社区参与；以及不太可能伪造数据，因为他们缺乏避免被发现的技能。本文对这些假设提出质疑。它借鉴了达斯顿的“科学角色”概念和法农的面具制作概念，探索田野工作人员如何在其有限的角色内构建身份和数据。现场工作人员为了获得和保住工作而创造出特定的假人或面具。他们简化简历，并以部分“真实”但也“虚假”的方式强调他们与社区成员的相似之处。这些构建的身份为现场工作人员提供了一个角色，使他们能够在不引起怀疑的情况下伪造或修改数据。他们经常从事被称为“真假”数据伪造的做法，即数据被认为实际上是正确的、可验证的，但在方法上是错误的，因此它在不同程度上是真实的和虚假的。我们将“伪”理解为真实与虚假之间的模糊空间，现场工作人员在此构建他们的身份和数据。鉴于全球健康看似值得称赞的目标，我们认为，现场工作人员掩盖和伪造数据表明，设计其研究的人员需要更加关注，以更好地理解和解决这些做法发生的原因和方式。
This paper centres on the roles and contributions of fieldworkers-local data-collectors in Global Health research in postcolonial contexts. It is informed by two separate ethnographies, conducted in two different East African biomedical research institutions. It discusses how common characterisations of fieldworkers as 'low-skilled' and 'local' make them attractive to research institutions in two important ways - as community-embedded data-collectors thus facilitating community participation and as being unlikely to fabricate data because they lack the skills to avoid detection. This paper questions these assumptions. It draws on Daston's idea of the 'scientific persona' and Fanon's concepts of mask-making to explore how fieldworkers construct identities and data within their liminal roles. Fieldworkers create particular pseudo-personae or masks for getting and staying employed. They dumb-down CVs and emphasise their similarities with community members in ways which are partially 'real' but also 'fake'. These constructed identities provide fieldworkers with a persona that allows them to fabricate or modify data without raising suspicions. They frequently engage in practices known as 'genuine fake' data fabrication which is data perceived as factually correct and verifiable yet methodologically incorrect, hence it is real and fake in varying degrees. We understand the 'pseudo' as the blurry space between real and fake where fieldworkers construct their identities and data. Given the seemingly laudable aims of Global Health, we argue that fieldworkers' masking and making up data signal the need for greater attention by those designing its research, to better understand and address why and how these practices unfold.