Demand for and Impact of Performance Audits on Public Administration in Kazakhstan
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Demand for and impacts of performance audits (PA) on public administration in Kazakhstan have not been studied. This information gap increases risks of missed government opportunities to improve public sector performance. Using new public management theory and the principal-agent model as guiding lenses, the purpose of this phenomenological study was to explore the demand for and effects of PA on Kazakhstanâs public administration. The research question explored the lived experiences and perceptions of the key participants and users of PAs, i.e., auditors, managers of auditees, and parliamentarians, and included reviews of over 200 official documents including audit reports and 14 semistructured interviews. Transcripts underwent inductive descriptive and conceptual coding, integrated application of bracketing and constructed thematic were used to generate and verify themes and patterns associated with PA demand and impact. Research findings illustrated that PAs are frequently requested in Kazakhstan due to problems in public administration, impacting positively and negatively those involved in PA, audit organizations, auditees, and contributing to improved budget process, laws, and regulations. Positive social change implications include providing information for parliamentarian decision-making on using responsive PA and for audit leaders and auditees on development strategies, fostering new performance auditor professional advancement. Additionally, new insights on influential PA triggers may help auditors undertake useful PA, while new PA impact information may support public policy leaders as they steadily improve citizensâ well-being through responsible government.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it