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Record W2591969146 · doi:10.1108/maj-04-2016-1368

Impact of performance audit on the Administration: a Belgian study (2005-2010)

2017· article· en· W2591969146 on OpenAlexaff
Ella Desmedt, Danielle Morin, Valérie Pattyn, Marleen Brans

Bibliographic record

VenueManagerial Auditing Journal · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicPublic Policy and Administration Research
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsAuditPerformance auditJoint auditAccountingChief audit executiveBusinessAudit evidenceAudit planInternal auditGovernment (linguistics)Public relationsPolitical science

Abstract

fetched live from OpenAlex

Purpose This study of the impact of Belgian Court of Audit on Federal Administration for the 2005 to 2010 period aims to highlight the auditors’ influence on the management of governmental organizations through the performance audits they have been conducting since 1998. A set of ten variables allows us to measure the three types of uses of performance auditors’ work by auditees: instrumental, conceptual and strategic use. Design/methodology/approach A survey was sent out to a total of 148 respondents identified by the authorities of the targeted organizations; 47 usable questionnaires were completed (32 per cent response rate). Findings The Court of Audit’s impact on the audited entities did not provoke radical changes in the auditees’ organizational life, but the intervention of the auditors was nevertheless noticeable. The nature of the impact was rather conceptual than strategic or instrumental. And the negative consequences on auditees anticipated in the literature were not observed. Research limitations/implications Given the five-year period covered by the study which was made in 2014 (four years after 2010), it had to deal with the mortality of respondents and the loss of organizational memory. Practical implications The study gives more accurate insights about the influence that Supreme Audit Institutions (SAIs) actually exert on audited Administrations through their performance audits. Originality/value Because SAIs have been mandated to evaluate the government’s economy, efficiency and effectiveness for almost 40 years in the Western democracies, it is mandatory that their actual ability to influence Administrations be documented more abundantly and independently by academic researchers.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.326
Threshold uncertainty score0.649

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.090
GPT teacher head0.418
Teacher spread0.328 · 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

Citations32
Published2017
Admission routes1
Has abstractyes

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