The Economic Value of Auditing and Its Effectiveness in Public School Operations*
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
We examine the impact of auditing on public school operations with two objectives: to investigate whether audits provide economic benefits to stakeholders, and how complex compliance rules impact auditing effectiveness. Utilizing auditing time data and a unique opportunity presented by the Quality Basic Education Act in Georgia, we estimate the relative performance of school district operations employing a stochastic frontier estimation technique. We find that auditing produces real economic benefits for stakeholders by mitigating inefficiency in the use of school resources. We also find that stringent compliance rules reduce an audit’s effectiveness but auditors’ experience can help to overcome the problems. The lack of disclosure of auditing costs hinders the ability to conduct a cost-benefit analysis of new requirements. Our analysis supports the notion that auditing is vital to establish governance mechanisms and disclosure of auditing costs is important to adequately evaluate a new policy.
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.
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 | 0.064 | 0.054 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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