Bibliographic record
Abstract
The balancing act between neutral accounting policies and accounting policies that take economic consequences into consideration has been on the agenda of accounting regulators and researchers since the 70s. The transition to fair value accounting in conjunction with the recent economic crisis have led to a revival of interest in this balancing act especially in the field of pension accounting. Due to the negative economic consequences anticipated by companies sponsoring defined benefit pension funds (e.g., decrease in owners’ equity), pension accounting has moved from an accounting that takes into consideration economic consequences to a more neutral accounting only gradually and not in a once-and-for-all event. This paper documents identified and anticipated economic consequences of recent pension accounting changes like shifts between different types of pension plans (from defined benefit to defined contribution), changes in the governance structure between the sponsoring organization and the pension fund (less accountability by pension fund), more incentives for earnings management, and changes in investments strategies by sponsoring organizations (from equity to bonds). Recent proposals for regulatory changes (i.e., IAS 19 revised) head towards an excessive conservatism and hence diminished neutrality. During and in the aftermath of the recent economic crisis – when interest rates are low – conservative pension accounting can have negative economic consequences if pension funds look as if they are underfunded and sponsoring companies present higher retirement related expenses. Shifts in the accounting policies that depart from neutrality and have negative economic consequences should be taken into consideration by regulators when issuing accounting standards.
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 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 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".