IPR-beachheads. Babcock & Wilcox's business and innovation strategies in Spain
Bibliographic record
Abstract
During the last quarter of the nineteenth century, American corporations began their multinational expansion to Europe through direct investments in the most-developed economies. Being increasingly aware of scientific and technological knowledge business value, they also began to develop early IPR international protection strategies in order to defend their intangible assets abroad. Before World War II, many of these multinationals had also reached lagging peripheral countries, resulting in a complex European network of subsidiaries and affiliates that has been scarcely studied. This paper delves into the Babcock & Wilcox entrepreneurial conglomerate – one of the most interesting case studies of early multinational expansion – to analyze how it arrived and developed in Spain, what its business and innovation strategies in that market were, and the role of patent management in that process. Our findings reveal that corporate interests in patent capture, control, and administration not only shifted research and innovation handling within firms but also led to quick learning on how to successfully use IPRs as business, legal, and organizational tools for international expansion.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".