Go and Chess as prognosis instruments for understanding competitive positions
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 Asians play Go and Europeans play Chess. These two games reflect the strategic thinking which is often typical of the Asian and the European manager. Whoever understands and masters the games will be better able to understand the competitive behaviour of their international competitors and secure competitive advantage. This paper deals primarily with the explanatory power of both board games for international business strategies of Japanese and European companies. While a strategy of sequential market entry is typical for many Japanese companies, European firms often prefer quick market entry by company takeovers. Many elements of strategy in the game of Go can be found again in Japanese firms: the strong position on the domestic market, the strategy of exercising restraint, the readiness to make strategic sacrifices, the development of a sense for the direction as well as strategic flexibility. In contrast, European firms often court market entry by acquisition. This strategy is also reflected in the game of Chess: the objective of destruction of the opponent requires an offensive strategy in the opposing sphere of influence, tactical skills and distinctive analytical skills. Copyright © 2003 John Wiley & Sons, Ltd.
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 | 0.001 | 0.000 |
| 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