Burdens of transparency: An analysis of public sector internal auditing
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
Abstract Transparency is largely seen as essential to public sector accountability. Yet, information disclosure also generates unintended consequences that may prove detrimental to the workings of some accountability processes. In this light, we investigate the views of Canadian public sector internal auditors, a subset of professionals fulfilling an important accountability function. We show that concerns surrounding disclosure requirements are prevalent. We demonstrate that internal auditors who see public disclosure requirements as a barrier to their effectiveness are more likely to be and/or perceive their organization to be risk averse, to feel professionally isolated and to favour a greater role for data analytics in accountability processes. However, auditors who would like to see their profession play a greater advisory role in their organization view public disclosure in a more positive light. We argue that understanding who is resisting helps identify threats to accountability mechanisms, improves the design of transparency policies and facilitates implementation.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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