Bibliographic record
Abstract
Abstract FAS 157, the U.S. accounting standard that prescribes how fair values of assets and liabilities are to be measured when other U.S. GAAP standards require fair valuation, stipulates that fair values be measured as the exit values of assets and liabilities—the proceeds for assets hypothetically sold on the date of the financial report, and, correspondingly, the amount required to settle liabilities on the date of the financial report. This conceptual article argues that exit values do not reflect the value of the net assets of the firm to shareholders, which is best reflected by discounted cash flows to maturity. Moreover, exit values—biasing fair values downward when markets are illiquid—have a pernicious, systemic risk effect; specifically, they give rise to write‐downs that in turn cause contagion: prices of equities and other financial instruments of peers react negatively, leading to further write‐downs by those peers. This may have aggravated the recent financial crisis. However, while exit values are not proper measures of value to shareholders, they are useful measures of downside risk when prospects turn sour for a firm. Thus, both exit values and discounted cash flows should be presented in financial statements.
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 | 0.025 | 0.151 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.002 | 0.016 |
| Scholarly communication | 0.014 | 0.022 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 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".