Briefing No. 6 - Financial Inequalities and the Pandemic
Bibliographic record
Abstract
Many households’ financial situation declined during the pandemic. 39% reported worse financial health, and just 16% better. Gaps have widened, with 52% of disadvantaged households reporting worse financial health, compared to 34% of others. 22% of professional households reported an improved financial situation, over twice that of working class households (10%). \n \nOne in ten young people (10%) were living in households classed as food insecure, with many reporting running out of food, skipping meals, and 5% of parents reporting going a whole day without eating. \n \nSocial renters were six times more likely to experience food insecurity than those who owned their home (26% vs 4%). Rates of food insecurity were highest in the North East and North West (15% and 12%), and lowest in the South East (9%) and East of England (7%). \n \n8% of parents used a food bank during the pandemic period, three quarters of whom had also used food banks pre-pandemic. Food poverty is not restricted to Free School Meals eligible families. The majority (57%) of households where children went hungry were not FSM eligible during that time, and 36% of those using foodbanks were not FSM eligible. \n \nPupils in families who reported using food banks during the pandemic received lower GCSE grades (almost half a grade per subject), even taking into account previous grades and other aspects of their household finances. However, long-term disadvantage played a bigger role than the pandemic. \n \nPandemic financial experiences were more closely linked to mental health. Among families finding it very difficult to get by financially, rates of psychological distress were 82% among parents, and 53% among children. Among parents this is four times higher than those living comfortably. \n \nRates of psychological distress were substantially higher in households who started using foodbanks in the pandemic (53% among young people and 63% among parents), compared to 41% and 33% for those not using foodbanks. They were also slightly higher than ‘long term’ users, potentially indicating the impacts of short-term financial shocks.
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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.024 | 0.018 |
| Insufficient payload (model declined to judge) | 0.080 | 0.018 |
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".