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Record W2160650630 · doi:10.1111/1468-0106.12084

Corruption in Public Procurement Market

2014· article· en· W2160650630 on OpenAlexaff
Tetsuro Mizoguchi, Nguyen Xuan Quyen

Bibliographic record

VenuePacific Economic Review · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicCorruption and Economic Development
Canadian institutionsUniversity of Ottawa
FundersJapan Society for the Promotion of Science
KeywordsBiddingProcurementQuality (philosophy)Product (mathematics)BusinessProduct marketIndustrial organizationRanking (information retrieval)Language changeMarket powerEconomicsFinanceMicroeconomicsMarketingMonopoly

Abstract

fetched live from OpenAlex

Abstract The paper presents a model of public procurement in which the contracting officer is corrupt and extracts bribes from the bidding firms. The firms submit multidimensional bids, which consist of the quality and the price of the project that they propose to realize. The firms differ in their costs of realizing the project at a given quality, and these costs are private information. The contracting official, in exchange for a bribe, abuses the power of his or her public office by distorting the quality ranking of the bids and by giving the favoured firm an opportunity to readjust its bid to undercut its rivals. Our analysis suggests that when the firms serve only the internal market, the public project is realized at low quality and inflated prices. However, when the firms are also allowed to sell the product they develop for the internal market in a foreign market, the auction is ex post efficient.

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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0020.006
Scholarly communication0.0070.006
Open science0.0010.002
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0160.001

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 head0.054
GPT teacher head0.305
Teacher spread0.251 · 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 designObservational
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

Citations16
Published2014
Admission routes1
Has abstractyes

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