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Record W4393277136 · doi:10.1177/2631309x241236202

Globalized Tax Evasion and Corruption: Two Steps Forward, One Step Back

2024· article· en· W4393277136 on OpenAlexafffund
Laureen Snider

Bibliographic record

VenueJournal of White Collar and Corporate Crime · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicCorruption and Economic Development
Canadian institutionsQueen's University
FundersSocial Sciences and Humanities Research Council
KeywordsTax evasionLanguage changeEvasion (ethics)BusinessEconomicsLaw and economicsPublic economicsPhilosophyLinguisticsMedicine

Abstract

fetched live from OpenAlex

This paper examines two classic crimes of the powerful, corruption and corporate tax evasion. It argues that tax avoidance/evasion is a type of corruption. Both are committed primarily by individuals and organizations with some combination of cultural, political and economic power, and this power means both sets of acts are difficult to trace, prosecute and punish. The paper begins with an analysis of corruption, as a behaviour, a label, and finally a set of legally proscribed acts. The focus then shifts to one type of corruption, corporate/elite tax evasion and avoidance. The goal of this article is to document the harm done by tax avoidance/evasion and assess possible remedies, while recognizing that “reforms” targeting the most powerful elites and corporations in the modern world will be heavily resisted at all stages of the legal process.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0020.020
Scholarly communication0.0070.014
Open science0.0010.006
Research integrity0.0050.010
Insufficient payload (model declined to judge)0.0050.001

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 head0.307
Teacher spread0.246 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations6
Published2024
Admission routes2
Has abstractyes

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