Socio‐political structures as determinants of global success
Bibliographic record
Abstract
Especially over the past decade, there have been numerous changes in the global marketplace which indicate that change is the only constant fact of life. These changes have increased not only opportunities but also uncertainty for organizations. The dynamic environment provides organizations with continuous feedback, to which they need to adapt. Past success masks the multinational corporation’s ability to perceive and respond to these changes. The key to survival in such a setting is culturally sensitive organizational learning. Strategic planning is necessary to cope with different levels of uncertainty encountered in foreign markets and to fully tap the new resources. Organizational effectiveness is directly influenced by the firm’s ability to achieve a “close‐fit” between the internal dynamics and the socio‐political structures. This, in turn, is possible through management practices sensitive to the local core cultural values. The Enron Power Project at Dabhol (Maharashtra, India) brings to light various socio‐political factors that have a direct impact on the organizational effectiveness, its survival and its long‐term success.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".