Bibliographic record
Abstract
We carried out a series of analyses of fuel poverty during the cost-of-living crisis, and also explored the potential impact of social tariffs. Since then, fuel prices have fallen, but they are still above pre-crisis levels, they increased in the last two quarters of 2024/25 and will increase again in the first quarter of 2025/26 by 6.4 per cent. At the same time, all mitigations have ended and the winter fuel allowance for pensioners has been restricted to pensioners on Pension Credit. This paper presents a revised analysis of who will be affected by fuel poverty in January 2025, based on analysis of the ONS Living Costs and Food Survey. We use a threshold of households spending more than 10 and 20 per cent of their net income after housing costs on fuel. The analysis describes their characteristics, fuel poverty rates, and fuel poverty gaps. We find that although there is a clear association between fuel poverty and net income, with fuel poverty concentrated in the lower-income deciles, some richer households also spend more than 20 per cent of their income on fuel, and 26.3% of households in fuel poverty are not income poor. Childless couples and couple pensioner households are less likely than average to be fuel poor, and couples with two or more children and lone parent households are more likely to be fuel poor.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.033 | 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".