To what extent do disadvantaged neighbourhoods mediate social assistance dependency? Evidence from Sweden
Bibliographic record
Abstract
Abstract This article investigates social assistance dependency and its relation to neighbourhood disadvantage in Sweden. We combine Swedish register data, tracking and analysing a cohort from 1998–2017, with the help of causal mediation, our analysis identifies the impact of early-adulthood social assistance on mid-adulthood social assistance. More specifically, we examine the mediating roles of neighbourhood conditions and compare this effect to the well-known mediating effect of unstable work experiences. Our findings suggest a differential effect for individuals with a high versus low probability of receiving social assistance in early adulthood. For individuals with a baseline high probability of receiving early-adulthood social assistance, the total estimated effect of early-adulthood social assistance on mid-adulthood social assistance recipiency is over 15 per cent points. Neighbourhood disadvantage only has a minor mediating effect on average, however, for individuals with a high risk of early-adulthood social assistance, the effect is substantial, over 5 per cent points, even more than the mediating effect from unstable work. The findings suggest that for high-risk individuals, social assistance recipiency in young adulthood is linked to subsequent entrenchment in disadvantaged areas and unstable employment, reinforcing a cycle of poverty. Our findings contribute to understanding the complex interactions between policy, socioeconomic status, and environmental factors in perpetuating social assistance dependency.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".