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Anticorruption

2020· book· en· W4237614949 on OpenAlexaboutno aff
Robert I. Rotberg

Bibliographic record

VenueThe MIT Press eBooks · 2020
Typebook
Languageen
FieldSocial Sciences
TopicCorruption and Economic Development
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical science

Abstract

fetched live from OpenAlex

Winning the anticorruption battle: a guide for citizens and politicians. The phenomenon of corruption has existed since antiquity; from ancient Mesopotamia to our modern-day high-level ethical morass, people have sought a leg up, a shortcut, or an end run to power and influence. In this volume in the MIT Press Essential Knowledge series, Robert Rotberg, a recognized authority on governance and international relations, offers a definitive guide to corruption and anticorruption, charting the evolution of corruption and offering recommendations on how to reduce its power and spread. The most important component of anticorruption efforts, he argues, is leadership that is committed to changing dominant political cultures. Rotberg explains that corruption is the conversion of a public good into personal gain—either by the exchange of cash for influence or by the granting of special favors even without explicit payments. He describes successful anticorruption efforts in countries ranging from Denmark and Sweden to Canada and Costa Rica, and discusses the roles of judicial systems, investigative journalism, multinational corporations, and technological advances. He shows how the United States has become more corrupt than before, and contrasts recent US and Canadian experiences. Without sufficient political will to eliminate corruption, it persists. Rotberg outlines thirteen practical steps for battling corruption, including removing holdover officials tainted by corruption and the public declaration of financial assets by elected officials and appointees.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.811
Threshold uncertainty score0.973

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.089
GPT teacher head0.295
Teacher spread0.206 · 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 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

Citations4
Published2020
Admission routes1
Has abstractyes

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