Accrual accounting by Anglo-American governments: Motivations, developments, and some tensions over the last 30 years
Bibliographic record
Abstract
This article takes a comparative international accounting history (CIAH) approach (Carnegie and Napier, 2002) to describe and discuss motivations for, and developments in the adoption of accrual accounting in five Anglo-American countries: Australia, Canada, New Zealand, the United Kingdom, and the United States. Although the adoption of accrual accounting across these countries over the last two decades can be attributed to the 1980s philosophy of new public management (NPM), the CIAH perspective illuminates similarities and differences in the nature of accrual accounting practices. The differences are due, in large part, to the timing and speed of change required by government, as well as the role played by the profession. Several tensions have arisen from the adoption of accrual accounting and these are also outlined. Given the inclusion of five countries and a span of 30 years, this article is necessarily in the nature of an overview.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".