Foreign Multinationals in the United States: Management and Performance
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
1. American Dreams 2. An Overview of Foreign Companies in the United States, 1945-2000 3. Revisiting UK FDI in US Manufacturing and Extractive Industries in 1960 4. Canadian Companies in the United States: A Survey and a Case Study 5. Siemens in the US 6. French Direct Investment in Car and Truck Manufacturing in the US: A Story of Failure and Success 7. Managing U.S. Subsidiaries from Non-Traditional Foreign Direct Investors: Spanish Stainless Steel Companies 8. Foreign Banks in the United States since World War II: A Useful Fringe 9. OLI and OIL: BP in the US in Theory and Practice, 1968-1998 10. The 'Americanization' of Shell Oil 11. What do Affiliate Exits Tell us about the Challenges Faced by Foreign Investors in the United States? 12. Management Archetypes and the Location Strategies of Japanese Multinationals in the US
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 | 0.001 | 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