The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Racial Threat and Partisan Identification
Open accessAbstract
Over the past three decades, as the Democratic party in the South has come to depend more heavily on black voters for its success, it has experienced a decline among white adherents.Power theory views relationships between groups as a function of their competitive positions in political, economic, and social arenas. In contexts where the threat posed by a minority group is high, the dominant group's response is predicted to be more hostile than in contexts where that threat is low. A pooled time series analysis of voter registration data for Louisiana parishes for 1975–90 provides support for the operation of the threat mechanism. Higher black concentrations are associated with declines in the percentage of white registered voters who are Democrats and an increase in the percentage who are Republicans. Consistent with the expectations of power theory, this relationship is conditioned by the social status of the parish.
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
Cites
Race Prejudice as a Sense of Group Position
Blumer, H. (1958) · The Pacific Sociological Review · doi:10.2307/1388607 · Cited by 3,487
Cited by
What To Do (and Not to Do) with Time-Series Cross-Section Data
Beck, N., & Katz, J. N. (1995) · American Political Science Review · doi:10.2307/2082979 · Cited by 6,840
Mason, L. (2015) · American Journal of Political Science · doi:10.1111/ajps.12089 · Cited by 1,458
McLaren, L. M. (2003) · Social Forces · doi:10.1353/sof.2003.0038 · Cited by 1,017
Nuisance vs. Substance: Specifying and Estimating Time-Series-Cross-Section Models
Beck, N., & Katz, J. N. (1996) · Political Analysis · doi:10.1093/pan/6.1.1 · Cited by 937
T IME-S ERIES–C ROSS-S ECTION D ATA: What Have We Learned in the Past Few Years?
Beck, N. (2001) · Annual Review of Political Science · doi:10.1146/annurev.polisci.4.1.271 · Cited by 916
Metadata
- Authors
- Giles, M. W., & Hertz, K.
- Venue
- American Political Science Review
- Publisher
- Cambridge University Press (CUP)
- Published
- 1994-06
- Volume
- 88
- Issue
- 2
- Pages
- 317-326
- ISSN
- 0003-0554 (ISSN-L)
- 1537-5943
- OpenAlex
- W2120623994
- Cited by
- 386
- References
- 1
- FWCI
- 30.71
- Type
- journal article
- Language
- en
- Open access
- bronze
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: Racial Threat and Partisan Identification. https://app.cochat.ai/papers/10.2307/2944706
- The paper
- Giles, M. W., & Hertz, K. (1994). Racial Threat and Partisan Identification. American Political Science Review. https://doi.org/10.2307/2944706
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.