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Record W2033470511 · doi:10.7202/1029057ar

Political Corruption, Democratic Theory, and Democracy

2015· article· en· W2033470511 on OpenAlexvenueno aff
Doron Navot

Bibliographic record

VenueLes ateliers de l éthique · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Philosophy and Ethics
Canadian institutionsnot available
Fundersnot available
KeywordsConceptualizationDemocracyPoliticsLanguage changeAbuse of powerHarmPolitical corruptionPolitical sciencePolitical economyInstitutionPower (physics)Law and economicsSociologyLaw

Abstract

fetched live from OpenAlex

According to recent conceptual proposals, institutional corruption should be understood within the boundaries of the institution and its purpose. Political corruption in democracies, prominent scholars suggest, is characterized by the violation of institutional ideals or behaviors that tend to harm democratic processes and institutions. This paper rejects the idea that compromises, preferences, political agreements, or consent can be the baseline of conceptualization of political corruption. In order to improve the identification of abuse of power, the concept of political corruption should not be related directly to democratic institutions and processes; rather, it should be related to ideals whose content is independent of citizens’ preferences, institutions and processes. More specifically, I articulate the relations between political corruption and the notion of subjection, and include powerful citizens in the category of political corruption. Yet, I also suggest redefining under what conditions agents are culpable for their motivations in promoting private gain. By doing this, we better realize how democratic institutions can be the source of corruption and not just its victims. Such a redefinition, I propose finally, is the basis for the distinction between individual and institutional corruption.

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.

How this classification was reachedexpand

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)0.003
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.848
Threshold uncertainty score0.559

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.061
GPT teacher head0.351
Teacher spread0.290 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations9
Published2015
Admission routes1
Has abstractyes

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