Bibliographic record
Abstract
The underlying pattern of growth over the course of last summer has proven difficult to interpret from the national accounts data. What at first appears to be a recovery, from the low rate of growth seen at the beginning of last year, gaining momentum over the summer, is instead likely to be an initial bounce back in the second quarter followed by further weakness in growth. The Office for National Statistics estimates that without the disruption associated with the Jubilee holiday, quarterly GDP growth would have decelerated from 0.8–1.3 per cent in the second quarter to 0.2–0.5 per cent in the third quarter last year. This is in contrast with the acceleration in growth from 0.6 to 0.9 per cent per quarter over the same period suggested by the national accounts, portraying a rather different picture of the economic recovery. Preliminary estimates of GDP suggest that the economy expanded by 0.4 per cent in the fourth quarter of last year. This is as we anticipated when preparing the forecast, which was completed before the fourth quarter estimates of GDP were released. Taken together, the figures for the fourth quarter and the estimates of growth in the absence of the disruption associated with the Jubilee holiday suggests that the recovery has been slow to gather pace in the second half of the year. In the year as a whole, GDP grew by an estimated 1.7 per cent.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.093 | 0.041 |
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".