Bibliographic record
Abstract
ABSTRACT Accounting for defined benefit pension plans has long been a major issue in accounting. Standard‐setters are grappling with revisions to pension accounting standards, and much change has already occurred in the United Kingdom. This paper identifies and discusses most of the major issues that standard‐setters must confront in developing new approaches to financial reporting for pensions. Key issues concern how to report the impact of changes in assumptions, how to recognize pension costs on the balance sheet and income statement, and how to reconcile the differences between accountants' and actuaries' approaches to pensions. Current standards assume that accounting estimates are independent of actuarial assumptions, and yet require a direct comparison of the accounting liability with the pension plan assets, when in fact they are incompatible measures based on differing assumptions and differing methodologies. As well, accounting has been complicit in managers' wishes to hide the volatility inherent in a pension plan investment strategy that focuses on higher‐risk equities to fund estimated monetary liabilities that have been discounted at low‐risk interest rates. Drawing on studies and research done largely in Europe, this paper attempts to consolidate some of the current thinking on the topic and to propose some preferred approaches to dealing with the problems of pension accounting.
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.
How this classification was reachedexpand
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 | 0.001 |
| 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 | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".