Strategic Operations Research and the Edelman Prize Finalist Applications 1989–1998
Bibliographic record
Abstract
In an earlier study we examined the available evidence on the Edelman Prize finalist applications 1989–1998. This study concluded that 13 of the 42 private sector applications provide examples of strategic operations research (SOR) when SOR is defined as operations research that creates a sustainable competitive advantage. In a follow-up study we tested our classifications, gathering longitudinal information on the continued success of the Edelman applications. We contacted people who were familiar with all the private sector applications that were Edelman finalists 1989–1996 and had at least five years of history since the competition. We describe the post-Edelman history of these applications and use this data to reassess their strategic role. We found that the longitudinal data provides evidence to support our original classification, but also suggests that several additional applications were more strategic than was originally apparent. We conclude that almost 60% (20 of 34) of these applications created a sustainable competitive advantage for their firms and provide examples of SOR.
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 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 | 0.009 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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 teacher head, 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".