Bibliographic record
Abstract
Abstract This paper argues that the current paradigm of value creation has led to a number of unacceptable outcomes. Exaggerated by executive compensation incentives focused on short‐term results, the model of shareholder wealth maximization spurs short‐term profits that fail to take into account those costs that are externalized to other stakeholders. We argue that the all‐inclusive costs can far exceed those explicitly accounted for and that their magnitude is often such that it outweighs the short‐term gains by a wide margin. The cascading nature of these costs, the growing voice of other stakeholders in support of their interests, the erosion of public trust, and the increasingly dire state of the global environment have accelerated the pace of calls for the adoption of a model of sustainable value creation—one in which shareholders’ wealth is maximized without making any of the other stakeholders significantly worse off. Taking an exploratory step toward developing such an ideal process, we present a simple example of a valuation model that incorporates such a principle. We also argue that markets, education, and regulation represent the three indispensable cornerstones of a sustainable value creation framework.
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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.021 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".