Bibliographic record
Abstract
Abstract In this paper I show that the aggregation of operating and financial income imposes three conditions on earnings‐based value functions. These three conditions provide a shortcut way to identify dividend irrelevant value functions. For example, consider any value function Vt of book value bt, earnings xt, and dividends dt. The aggregation conditions imply that Vt must be of the form Vt = (1 − k)bt + k [f xt − dt]. f is the permanent earnings capitalization factor and undetermined weight k may be any function of Δt ≡[φxt − dt] − bt. The Ohlson 1995 model is the special case when k is constant. But generally k does not have to be constant to maintain dividend irrelevancy. Whenk varies with Δt, Vt is nonlinear in earnings. Hence, this result specifies how Vt may be nonlinear in earnings in settings with limited liability or production or abandonment options and still be dividend‐irrelevant. An even more remarkable feature of this result is that it holds whether accounting is clean surplus or not. One must conclude that accounting‐based valuation properly builds from accounting aggregation and Δt, and not from the clean surplus relation and abnormal earnings as many now believe.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".