The DOI matches its Crossref record.
New York University Law Review
Abstract
In a society marked by a pluralism of comprehensive moral views, the ability of a constitutional regime to maintain widespread allegiance is due to “overlapping consensus.” Those with divergent comprehensive views may nonetheless agree on a given political conception of justice. However, the idea of an overlapping consensus, as used in Professor Rawls’s earlier works, has caused some misgivings. It seems to suggest that political philosophy is “political” in the wrong way. Professor Rawls answers these misgivings. A political conception of justice, such as Rawls’s “justice as fairness” in A Theory of Justice, is not merely tailored by the dominant group to justify favored results. Nor does it presuppose any particular comprehensive doctrine, whether religious or philosophical. Rather, as supported by an overlapping consensus, justice as fairness falls into a special domain of the political. It gives the framework of a stable constitutional regime by resting on the consensus of citizens who share an understanding of the role of certain basic rights and liberties, even though they may not agree on comprehensive doctrines .
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Bernal, D. D. (2002) · Qualitative Inquiry · doi:10.1177/107780040200800107 · Cited by 1,524
“But the data is already public”: on the ethics of research in Facebook
Zimmer, M. (2010) · Ethics and Information Technology · doi:10.1007/s10676-010-9227-5 · Cited by 900
What is data justice? The case for connecting digital rights and freedoms globally
Taylor, L. (2017) · Big Data & Society · doi:10.1177/2053951717736335 · Cited by 802
Ethical Implications and Accountability of Algorithms
Martin, K. (2019) · Journal of Business Ethics · doi:10.1007/s10551-018-3921-3 · Cited by 757
Dobbie, W., Goldin, J., & Yang, C. S. (2018) · American Economic Review · doi:10.1257/aer.20161503 · Cited by 564
Metadata
- Authors
- Rawls, J.
- Venue
- Justice
- Publisher
- Routledge
- Published
- 2017-07-12
- Pages
- 227-249
- OpenAlex
- W2962975506
- Cited by
- 2,872
- References
- 0
- FWCI
- 1166.59
- Type
- book chapter
- Language
- en
- Open access
- closed
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.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: New York University Law Review. https://app.cochat.ai/papers/10.4324/9781315193496-11
- The paper
- Rawls, J. (2017). New York University Law Review. Justice. https://doi.org/10.4324/9781315193496-11
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.