Safeguarding Data
The Data Consensus and the Public Good in Children's Social Services
Bibliographic Data
| ID | 4380259 |
|---|---|
| Authors | J Cearns (0000-0001-6498-1766, corresponding author), H Knox (0000-0003-2294-0258) |
| Year | 2024 |
| Volume | 42 |
| Issue | 1 |
| Pages | 23-41 |
| Publication date | 2024-03-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | The Cambridge Journal of Anthropology (JOURNAL) |
| Journal identifiers | ISSN: 0305-7674 • E-ISSN: 2047-7716 |
| Publisher | Berghahn Books (PUBLISHER • GB) |
| DOI | 10.3167/cja.2024.420103 |
| OpenAlex | W4396836906 |
| Language | EN |
| Citations received | 1 |
| References cited | 33 |
Over the past decade, data-driven systems have transformed how UK public services engage with the population. This ethnographic study, conducted in one of the United Kingdom's poorest boroughs, investigates the implementation of a machine learning data system for identifying at-risk children in need of safeguarding. It examines the concept of a 'data consensus' amongst council workers pursuing the 'public good'. Within this consensus, the article explores contrasting stances on data's potential, namely that of data scientists, who use it as a tool to predict human behaviour and prevent harm, and social workers, who resist the notion that a person is predictable and therefore incapable of change. This reveals the political implications of these opaque algorithmic systems as various groups harness data in the name of public benefit
Engineering ethics · Political science · Safeguarding · Engineering · Ethics in Clinical Research · Medicine · Nursing
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| Unique citing works | 1 |
|---|---|
| Citations per year | 1 |
| Citation span | 2025 - 2025 (1) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 1 |