Impact of host‐country corruption on U.S. and Chinese cross‐border acquisitions
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 Does corruption in a target country create a similar effect on cross‐border acquisitions (CBAs) by firms from a developed and a developing country? This article empirically examines the relationship between corruption and CBAs by firms from China and the United States. Based on a combined sample of 10,236 completed acquisitions over the period of 1990–2006, the authors find that both Chinese and U.S. firms make a significantly greater number of acquisitions in less corrupt countries. However, unlike the U.S. CBAs, we find a significantly positive relationship between the transaction value of Chinese CBAs and the level of perceived corruption in the target country. It is suggested that having been schooled in weaker institutions themselves, Chinese firms may find it easier to deal with corrupt conditions in target countries, giving them an advantage over firms from less corrupt countries. © 2010 Wiley Periodicals, Inc.
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 | 0.000 | 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) | 0.008 | 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