Cited by 16Academic integrity and plagiarismCorruption and Economic Developmentscientometrics and bibliometrics research

The real costs of plagiarism: Russian governors, plagiarized PhD theses, and infrastructure in Russian regions

Abalkina, Anna, Libman, Alexander·2020·Scientometrics

Integrity signals

Registry

Crossref · 10.1007/s11192-020-03716-x

Cites

101 of 101 references verified0 citation errors · 0 not checkable

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Cites

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Authors
Abalkina, A., & Libman, A.
Affiliations
  • Ludwig-Maximilians-Universität München (DE)
  • National Research University Higher School of Economics (RU)
Corresponding author
Abalkina, Anna
Venue
Scientometrics
Published
2020-10-24
Volume
125
Issue
3
Pages
2793-2820
ISSN
  • 0138-9130 (ISSN-L)
  • 1588-2861
OpenAlex
W3094262917
Cited by
16
References
103
Citations by year
2026: 1 · 2025: 2 · 2024: 4 · 2023: 1 · 2022: 7 · 2021: 1
FWCI
3.07
Type
journal article
Language
en
Open access
closed
Locations
  • Scientometrics (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
Funders
Basic Research Program of the National Research University–Higher School of Economics
Topics
  • Social Sciences › Safety Research › Academic integrity and plagiarism
  • Social Sciences › Sociology and Political Science › Corruption and Economic Development
  • Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › scientometrics and bibliometrics research
Keywords
plagiarism, PhD theses, regional governors, political performance, infrastructure development, housing construction, broadband, management skills, dishonest behavior, Russian regions

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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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