Bibliographic record
Abstract
Brexit was the epithet for “British Exit” from EU, the financial and strategy blending of which the U.K. had been an associate since 1973. That voted to leave the EU. The occupants decided that the assistances of free trade were not counterpoise the costs of free crusade of settlement. The vote was 17.4 million in favour of parting vs. 16.1 million who chosen to persist. For Europe, the negative consequences and defies of Brexit go approach elsewhere the GDP effect: the EU vanished about once sixth of its economic power and a far bigger share of its external and security policy weight with the exit of a nation which has significant global influence. For the UK, non-tariff obstacles are even more challenging than for the EU. Even if the UK signs trade covenants with other nations, the indication that profounder profitable conversation with the US, India, Australia, New Zealand, Canada of Japan could counter poise mislaid trade with the EU is ambiguous.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".