The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Ethical and Socially-Aware Data Labels
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“These problems arise due to, in large part, sensitive attributes embedded in data sets which are used by machine learning algorithms to search for patterns (Beretta et al., 2018).”
From Data governance: Organizing data for trustworthy Artificial Intelligence (2020) · cites this paper as Beretta et al., 2018
Citations
Cites
Barocas, S., & Selbst, A. D. (2014) · doi:10.2139/ssrn.2477899 · Cited by 3,048
Gebru, T., Morgenstern, J., Vecchione, B., Vaughan, J. W., Wallach, H., Daumé, H., & Crawford, K. (2018) · arXiv · doi:10.48550/arxiv.1803.09010 · Cited by 2,474
Gebru, T., Morgenstern, J., Vecchione, B., Vaughan, J. W., Wallach, H., III, H. D., & Crawford, K. (2021) · Communications of the ACM · doi:10.1145/3458723 · Cited by 2,469
Accountability of AI Under the Law: The Role of Explanation
Doshi-Velez, F., Kortz, M., Budish, R., Bavitz, C., Gershman, S. J., O'Brien, D., Scott, K., Shieber, S., Waldo, J., Weinberger, D., et al. (2017) · doi:10.2139/ssrn.3064761 · Cited by 457
On the (im)possibility of fairness
Friedler, S. A., Scheidegger, C., & Venkatasubramanian, S. (2016) · arXiv · doi:10.48550/arxiv.1609.07236 · Cited by 247
The Tyranny of Data? The Bright and Dark Sides of Data-Driven Decision-Making for Social Good
Lepri, B., Staiano, J., Sangokoya, D., Letouzé, E., & Oliver, N. (2017) · Studies in Big Data · doi:10.1007/978-3-319-54024-5_1 · Cited by 111
Self-citationHow to Address the Data Quality Issues in Regression Models: A Guided Process for Data Cleaning
Corrales, D., Corrales, J., & Ledezma, A. (2018) · Symmetry · doi:10.3390/sym10040099 · Cited by 58
Research works printed but not linked: 7
- Dwork, C., Hardt, M., Pitassi, T., Reingold, O., Zemeln, R.: Fairness through awareness. In: Proceedings of the 3rd Innovations in Theoretical Computer Science Conference, pp. 214–226. ACM (2012) · DOI · Paper page
- Hardt, M., Price, E., Srebro, N.: Equality of opportunity in supervised learning. In: Advances in Neural Information Processing Systems (2016)
- Hosni, H., Vulpiani, A.: Forecasting in light of big data. Philos. Technol. 13, 1–13 (2017)
- Karim, N.S.A., Ammar, F.A., Aziz, R.: Ethical software: integrating code of ethics into software development life cycle. In: 2017 International Conference on Computer and Applications (ICCA), pp. 290–298, September 2017. https://doi.org/10.1109/COMAPP.2017.8079763 · DOI
- O’Neil, C.: Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. Crown Publishing Group, New York (2016)
- Torchiano, M., Vetrò, A., Iuliano, F.: Preserving the benefits of open government data by measuring and improving their quality: an empirical study. In: 2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC), vol. 1, pp. 144–153, July 2017. https://doi.org/10.1109/COMPSAC.2017.192 · DOI
- Vetrò, A., Canova, L., Torchiano, M., Minotas, C.O., Iemma, R., Morando, F.: Open data quality measurement framework: definition and application to open government data. Gov. Inf. Q. 33(2), 325–337 (2016). https://doi.org/10.1016/j.giq.2016.02.001 · DOI
Cited by
Sorted by citations
Data governance: Organizing data for trustworthy Artificial Intelligence
Janssen, M., Brous, P., Estevez, E., Barbosa, L. S., & Janowski, T. (2020) · Government Information Quarterly · doi:10.1016/j.giq.2020.101493 · Cited by 811
Hutchinson, B., Smart, A., Hanna, A., Denton, R., Greer, C., Kjartansson, O., Barnes, P., & Mitchell, M. (2021) · Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency · doi:10.1145/3442188.3445918 · Cited by 279
Metadata
- Authors
- Beretta, E., Vetrò, A., Lepri, B., & De Martin, J. C.
- Venue
- Communications in Computer and Information Science
- Publisher
- Springer International Publishing
- Published
- 2019
- Pages
- 320-327
- ISSN
- 1865-0929
- 1865-0937
- Cited by
- 6
- References
- 7
- Language
- en
- Licence
- www.springer.com/tdm (tdm)
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Ethical and Socially-Aware Data Labels. https://app.cochat.ai/papers/10.1007/978-3-030-11680-4_30
- The paper
- Beretta, E., Vetrò, A., Lepri, B., & De Martin, J. C. (2019). Ethical and Socially-Aware Data Labels. Communications in Computer and Information Science. https://doi.org/10.1007/978-3-030-11680-4_30
