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Record W4406737212 · doi:10.23912/9781915097415-5863

Introduction

2024· book-chapter· en· W4406737212 on OpenAlexaff
William O’Toole

Bibliographic record

VenueGoodfellow Publishers eBooks · 2024
Typebook-chapter
Languageen
FieldSocial Sciences
TopicCorruption and Economic Development
Canadian institutionsInternational Development Research Centre
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

The generally accepted definition of corruption is the abuse of entrusted power for private gain. A more detailed definition is found in the AS 8001-2021: Fraud and Corruption Control, definition 1.4.8 “ dishonest activity in which a person associated with an organisation (e.g. director, executive, manager, employee or contractor) acts contrary to the interests of the organisation and abuses their position of trust in order to achieve personal advantage or advantage for another person or organisation. This can also involve corrupt conduct by the organisation, or a person purporting to act on behalf of and in the interests of the organisation, in order to secure some form of improper advantage for the organisation either directly or indirectly.” Australian Standards. (2001)

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.605
Threshold uncertainty score0.863

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0060.005
Open science0.0020.003
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.3950.225

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 head0.024
GPT teacher head0.247
Teacher spread0.223 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2024
Admission routes1
Has abstractyes

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