Bibliographic record
Abstract
The latest UK recession began in the April–June quarter of 2008. It was the longest recession on record nationally. By January 2010 the UK was, technically, out of recession and, in the words of the Chancellor of the Exchequer, Alistair Darling, ‘we are on a path to recovery’. But, as the Chancellor qualified in an announcement on 26 January, ‘I'm confident but I'll always remain cautious’. Darling's note of caution is quite right, for as many commentators have indicated, this is an extremely lacklustre recovery (BBC, 2010). Germany and France, Europe's two largest economies, came out of recession during the summer of 2009, followed by the United States. The latest economic figures from the UK, however, show a much limited upward trend, and the risk remains that the economy could dip back into recession. The technical calculations remain with the Office for National Statistics which is expected to publish final figures in March 2010.
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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 | 0.010 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.009 |
| Scholarly communication | 0.008 | 0.012 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.015 | 0.017 |
| Insufficient payload (model declined to judge) | 0.029 | 0.002 |
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".