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Record W4225101059 · doi:10.1080/10999922.2022.2046968

State Capture in South Africa and Canada: A Comparative Analysis

2022· article· en· W4225101059 on OpenAlexaboutno aff
Tryna van Niekerk, Anaïs Valiquette L’Heureux, Natasja Holtzhausen

Bibliographic record

VenuePublic Integrity · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicPolitical Influence and Corporate Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsAccountabilityLanguage changePoliticsPhenomenonPolitical corruptionState (computer science)Political sciencePolitical economyDemocracyDevelopment economicsEconomic JusticePublic administrationEconomicsLaw

Abstract

fetched live from OpenAlex

Corruption in all its forms, from bribery to influence and distortion of oversight, accountability and justice systems, in order to protect the criminal behavior of functionaries (public officials and political officials) is a global phenomenon. Corruption as a phenomenon is found in well-established democracies such as Canada, and is often endemic in young democracies such as South Africa, who fall into a cycle of political corruption and administrative accountability avoidance. What are the cross-cutting risk factors and mitigation factors that shape the functionality of anti-corruption mechanisms? This comparative analysis of corruption and state capture provides insight into the functionality of oversight, anti-corruption and accountability mechanisms in both countries. Findings indicate that both Canada and South Africa are at risk of the erosion of safeguards and at risk of the deterioration of the levels of vigilance required to prevent state capture.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.930
Threshold uncertainty score0.505

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0070.019
Science and technology studies0.0090.002
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.055
GPT teacher head0.244
Teacher spread0.189 · 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 designQualitative
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

Citations5
Published2022
Admission routes1
Has abstractyes

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