Accountability Disclosures by Queensland Local Government Councils: 1997–1999
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
The annual report is promoted and regarded as the primary medium of accountability for government agencies. In Australia, anecdotal evidence suggests the quality of annual reports is variable. However, there is scant empirical evidence on the quality of reports. The aim of this research is to gauge the quality of annual reporting by local governments in Queensland, and to investigate the factors that may contribute to that level of quality. The results of the study indicate that although the quality of reporting by local governments has improved over time, councils generally do not report information on aspects of corporate governance, remuneration of executive staff, personnel, occupational health and safety, equal opportunity policies, and performance information. In addition, the results indicate there is a correlation between the size of the local government and the quality of reporting but the quality of disclosures is not correlated with the timeliness of reports. The study will be of interest to the accounting profession, public sector regulators who are responsible for the integrity of the accountability mechanisms and public sector accounting practitioners. It will form the basis for future longitudinal research, which will map changes in the quality of local government annual reporting.
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 | 0.002 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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