Bibliographic record
Abstract
It is indispensable to assess how trade and FDI among the UK and the rest of world would be affected post-Brexit. This paper investigates how Brexit will affect exports and FDI from China, EU, and the US to the UK economy. Using econometric models with time series quarterly data for the period of 2001 through 2017 the results of this quantitative study indicate that Brexit will have significant impacts on trade and FDI from China, the United States, and EU to the UK. The topic is of great importance because it has severe consequences not only for the UK economy but also for the rest of the world. The quantitative results of this study suggest that Brexit has a negative statistically significant impact on trade and FDI from the EU and the US to the UK; however, trade and FDI from China will increase post-Brexit since China is highly integrated into the UK economy and has already established close trade relationships with the UK through mergers and acquisitions in recent years.
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How this classification was reachedexpand
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".