Cultural, administrative, and economic proximity between the UK and Canada should be good for trade
Bibliographic record
Abstract
Economists place considerable emphasis on the role of (geographic) distance in explaining the pattern of international trading relationships. Using a metaphor from Newtonian physics, trade and foreign direct investment (FDI) between countries are often seen as being driven by the forces of gravity, encapsulated in the relative size of their markets and the distance between their economies. Moreover, as shown in a previous brief, geographic distance is expected to have non-linear effects; as countries become further away, their trading relationship is expected to become less intense at an increasing rate. Building on that, in this post, Saul Estrin, Angelina Borovinskaya, Christine Cote, and Daniel Shapiro provide a more fine-grained perspective on gravity effects which takes into account administrative and economic differences as well as cultural factors. They argue that cultural, administrative, and economic proximity between the UK and Canada should be good for trade.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.011 | 0.011 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".