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
In the context of austerity‐inspired reforms to public audit in England we investigate the extent to which audit firms mitigate management bias in public sector financial reports. A substantial body of literature finds that both public and not‐for‐profit managers manage ‘earnings’ to report small surpluses close to zero by managing deficits upwards and surpluses downwards. Under agency theory, auditors acting in the interests of their principal(s) would tend to reverse this bias. We exploit privileged access to pre‐audit financial statements in the setting of the English National Health Service (NHS) to investigate the impact of audit adjustments on the pre‐audit financial statements of English NHS Foundation Trusts over the period 2010–2011 to 2014–2015. We find evidence that auditors act to reverse management bias in the case of Trusts with a pre‐audit deficit, but find no evidence that this is the case for Trusts with a pre‐audit surplus. In the case of Trusts in surplus, these findings are consistent with auditors’ interests being aligned with management, rather than principals.
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 | 0.000 | 0.002 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.005 |
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