Amna Batool
University of Michigan, Ann Arbor, Michigan, United States
Front-line workers in global development are often responsible for data collection and record-keeping about their own work. The authenticity of such data and the role of mid-level supervisors, however, remains understudied. We report on the case of immunization in Pakistan, where, through interviews with 30 mid-level vaccination managers in Punjab district, we find that data falsification by vaccinators is common, though not necessarily rampant. Because of an intricate protocol for record-keeping, supervisors can detect data falsification, and we find they have devised an array of methods, broadly classifiable into four types: triangulation, supplementary data collection, anomaly detection, and interrogation. We also find that the strategies that supervisors use to detect falsification seem linked to their style of management, with authoritarian supervisors preferring supplementary data collection and spot checks, while supportive supervisors use triangulation. Our findings lead to recommendations for designing technologies intended to monitor and manage front-line data.
https://doi.org/10.1145/3411764.3445630
The ACM CHI Conference on Human Factors in Computing Systems (https://chi2021.acm.org/)