Doing Business in the United States and Canada
Bibliographic record
Abstract
The U.S. is a great country – likely the world’s most powerful – but as a trading nation, it is less so. When your country is so powerful, it’s less important for you to adapt to the expectations of others. You expect them to adapt to you. If, however, you are not offering exactly what they want and make no effort to put others at ease, you may encounter more difficulties. American business negotiators place a lower premium on trust-based and long-term loyal business relationships. Their negotiation style is often competitive rather than cooperative. They are fiercely combative in trying to achieve the best terms they can and make no effort to give or save others’ face. It’s not a common style except, perhaps, in parts of Western Europe. It is, perhaps, a testament to the quality of Canadian business negotiators that, in 2019, over 75.3 percent of Canadian trade was with the United States, and Canada achieved a $2.4 billion trade surplus. 1
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.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.009 |
| Science and technology studies | 0.021 | 0.004 |
| Scholarly communication | 0.011 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.017 | 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".