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Record W3122375694

Searching for Electoral Irregularities in an Established Democracy: Applying Benford’s Law Tests to Bundestag Elections in Unified Germany

2011· article· en· W3122375694 on OpenAlex
Christian Breunig, Achim Goerres

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueKölner Universitäts PublikationsServer (Universität zu Köln) · 2011
Typearticle
Languageen
FieldMathematics
TopicBenford’s Law and Fraud Detection
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBenford's lawPrecinctDemocracyGermanPolitical scienceVariation (astronomy)State (computer science)LawLaw and economicsPublic administrationPolitical economyEconomicsGeographyPoliticsStatisticsComputer science
DOInot available

Abstract

fetched live from OpenAlex

This article investigates electoral irregularities in the 1990 to 2005 Bundestag elections of unified Germany. Drawing on the Second-Digit Benford Law (2BL) by Mebane (2006), the analysis consists of comparing the observed frequencies of numerals of candidate votes and party votes at the precinct level against the expected frequencies according to Benford’s Law. Four central findings stand out. First, there is no evidence for systematic fraud or mismanagement with regard to candidate votes from districts where fraud would be most instrumental. Second, at the state level (Bundesland), there are 51 violations in 190 tests of the party list votes. Third, East German states are not more prone to violations than Western ones. This finding refutes the notion that the East’s more recent transition to democracy poses problems in electoral management. Fourth, a strong variation in patterns of violation across Bundesländer exists: states with dominant party control are more likely to display irregularities. The article concludes by hypothesizing and exploring the notion that partisan composition of nominees involved in the counting may produce a higher likelihood of violation and be a cause of Länder variation. This may especially be the case when a party dominates in a Bundesland or opponents to the former socialist regime party are involved in the counting.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.216
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0000.011
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.093
GPT teacher head0.298
Teacher spread0.205 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it