Box A:An Alternative UK Economic Forecast
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The current economic environment in the United Kingdom is fraught with uncertainty, driven by a range of factors: from the geopolitical risks posed by the war in Ukraine, disruptive implications of a second Trump administration in the United States, an expansionary budget, and proposed changes to the planning system for housing and development. These challenges have created an unpredictable economic landscape in the United Kingdom. Our new multi-recurrent neural network forecasts provide fresh insights into key economic variables, including inflation, GDP and UK 10-year gilt yields for the coming year. The models indicate that inflation will rise modestly in the near term before accelerating over the longer run. In addition, GDP is expected to contract slightly in the first quarter of the year, with growth remaining sluggish throughout the remainder of the period. Meanwhile, UK 10-year gilt yields are predicted to experience an initial spike, followed by a period of stabilization. In this article, we present an economic outlook for the period from December 2024 to November 2025, highlighting the latest projections for inflation, GDP, and 10-year gilt yields. We can think of this as an alternative to the NIESR forecasts presented elsewhere in this UK Economic Outlook. We then review our past forecasting performance through a retrospective analysis of our CPI inflation forecasts since May 2024.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it