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
This paper is a follow-up of the article ‘Fudged Accounting Theory: Evidence from the UK’ in the Journal of Management Research (Ong, 2003). In that article, an analysis of the flexibility within the UK regulations, which allowed companies to use different accounting treatments for intangible assets, was illustrated to support fudged accounting theory (Murphy, 1990). This paper extends that earlier work by examining the association between corporate leverage and accounting choice in the UK at a period when the extant accounting standard for goodwill, SSAP22 Accounting for Goodwill (ASC, 1989), permitted two very different accounting treatments. As a result, other intangibles, particularly brands, could avoid the regulatory strictures. For the present study, a series of hypotheses relating to corporate leverage and capitalization of intangible assets were tested. The results of the present study support fudged accounting theory by providing evidence that there is a relationship between the widespread capitalization of goodwill/brands and the relationship with leverage. The results demonstrate that financial managers will tend to adopt accounting practices that result in stronger balance sheets.
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 | 0.007 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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