Further thoughts on the relationship between economic value added and stock market performance
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
Abstract As authors of a previous study questioning the strength of the relationship between EVA and shareholder value, and in light of the arguments posed by Keefe and Roush, we revisit the relationship between EVA and shareholder return and reexamine the evidence and issues surrounding the use of EVA as a tool for valuing investments. Using the Stern Stewart Fortune 1000 data, we examine two potential relationships for 33 food companies listed in the database. The first is between the absolute level of EVA in 2000 and 3‐, 5‐, and 10‐year shareholder returns. The second is between 3‐, 5‐, and 10‐year mean percentage changes EVA and 3‐, 5‐, and 10‐year shareholder returns. The correlations found were extremely weak in all instances tested. [EconLit citations: 9120, 9320, M410, Q130]. © 2003 Wiley Periodicals, Inc. Agribusiness 19: 255–267, 2003.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 it