Fudged accounting theory, Evidence from the UK
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 topic of accounting for intangible assets such as trade marks, patents, brands and goodwill has been highly controversial in the accounting profession for many years. Furthermore, the accounting treatment of brands has importance for marketers. Until recently, the flexibility within the regulations allowed companies to use a variety of accounting treatment and this led to the generation of fudged accounting theory (Murphy, 1990). This empirical study based on recent accounting regulatory changes for intangible assets in the UK examines the validity of the theory in the food, drink and media industries. The analysis demonstrates that companies are moving from the capitalization of brands to that of goodwill. Policies in respect of amortisation are, however, more divergent and fudged accounting theory still applies. The UK approach is being regarded with interest by the International Accounting Standards Committee and fudged accounting theory may be generalisable in different accounting regimes.
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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 | 0.012 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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