Bibliographic record
Abstract
The outlook for the Scottish and UK economies has weakened, with growth now expected to remain sluggish through the rest of 2025, according to the Fraser of Allander Institute at the University of Strathclyde. In its latest quarterly Economic Commentary, the Institute has downgraded its forecasts for Scottish economic growth to 0.8% in 2025 and 1% in 2026. This comes despite more upbeat projections from both the Scottish Fiscal Commission (SFC) and the Office for Budget Responsibility (OBR), which have recently upgraded their expectations for 2026 whilst similarly revising down their GDP forecasts for 2025. Economic growth is now slowing compared to the start of the year and inflation has also edged up to 3.4%, after staying below 3% throughout 2024. The business environment is also showing signs of strain, with companies reporting cutting back on activities in the first quarter compared to last year, plagued by rises in National Insurance Contributions, which took effect in April, alongside uncertainty surrounding President Trump’s trade tariffs. Indeed, pay growth and employee numbers are down, signalling potential weaknesses in the labour market. The current state of the economy was not unexpected: Institute Director Professor Mairi Spowage warned of turbulent and uncertain conditions which could last throughout the year in the previous commentary. Professor Spowage said: “After a strong start to the year, the Scottish economy has faltered in March and April and is essentially the same size in real terms as it was six months ago. “Unfortunately, the wider business environment and global events are still taking a toll on businesses and consumers, which is having a dampening effect on spending and business investment.” In addition to the latest economic analysis, the commentary provides an overview of Universal Credit and Legacy Benefits in Scotland, a key element of the nation’s social security system, and summarises key takeaways from June’s spending review and medium-term financial strategy. Dr Joao Sousa, Deputy Director of the Institute, said: “The fiscal announcements by both governments suggest that there are significant economic challenges in the years and months to come for the UK and Scottish Governments. “Particularly from 2027-28 onwards, the choices of Government look to become more difficult. Of course, this is the role of the Government in power: but the difficulties of the UK Government this week show that events can quickly derail its plans.”
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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 | 0.004 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.032 | 0.027 |
| Insufficient payload (model declined to judge) | 0.095 | 0.056 |
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".