research-article

Engaging Solidarity in Data Collection Practices for Community Health

Authors:

Neha KumarAuthors Info & Claims

Proceedings of the ACM on Human-Computer Interaction, Volume 2, Issue CSCW

Article No.: 76, Pages 1 - 24

https://doi.org/10.1145/3274345

Published: 01 November 2018 Publication History

Abstract

Researchers and practitioners engaged in global health are increasingly turning to data-driven approaches. However, the institutionalized roles and responsibilities---as well as motivations and workflows---of those involved in data collection are not well understood. To attain a deeper understanding of the practices of frontline health workers engaged in data collection, we conducted fieldwork in underserved contexts of Delhi, India. In particular, we interviewed these workers and observed their interactions with 200 households. Our analysis takes a postcolonial feminist perspective to examine how these frontline health workers navigate the multiple demands placed on them by their families, society, local residents, and health organizations. We also discuss how they practice feminist solidarity, and distill lessons for improved data collection across global health initiatives.

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Index Terms

Engaging Solidarity in Data Collection Practices for Community Health
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. Empirical studies in HCI

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cover image Proceedings of the ACM on Human-Computer Interaction

Proceedings of the ACM on Human-Computer Interaction Volume 2, Issue CSCW

November 2018

4104 pages

EISSN:2573-0142

DOI:10.1145/3290265

Editors:
Karrie Karahalios
University of Illinois & Adobe
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Andrés Monroy-Hernández
Snap Inc.
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Airi Lampinen
Stockholm University
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Geraldine Fitzpatrick
Vienna University of Technology

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Published: 01 November 2018

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Ming JGong DNgai CSterling MVashistha ADell N(2024)Wage Theft and Technology in the Home Care ContextProceedings of the ACM on Human-Computer Interaction10.1145/36374288:CSCW1(1-30)Online publication date: 26-Apr-2024
https://dl.acm.org/doi/10.1145/3637428
Chandhiramowuli STaylor AHeitlinger SWang D(2024)Making Data Work CountProceedings of the ACM on Human-Computer Interaction10.1145/36373678:CSCW1(1-26)Online publication date: 26-Apr-2024
https://dl.acm.org/doi/10.1145/3637367
Jo EJeong YPark SEpstein DKim Y(2024)Understanding the Impact of Long-Term Memory on Self-Disclosure with Large Language Model-Driven Chatbots for Public Health InterventionProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642420(1-21)Online publication date: 11-May-2024
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