Family income and child cognitive and behavioural development in the United Kingdom: does money matter?
Bibliographic record
Abstract
This study investigates the extent to which family income is associated with an extensive range of child cognitive and behavioural outcomes in a cohort of almost 19 000 British children born between 2000 and 2001. Merging the economists' and developmental psychologists' approaches, it also attempts to identify the main mechanisms through which family economic resources translate into better developmental outcomes for children. The relative and joint relevance of three groups of mediating factors (parental stress, parental investment and other family-related pathways), identified from the recent economic and psychological literature, are examined both in a cross-sectional ('mopping-up' approach) and in a panel data (fixed effects models) context. Results indicate a weak or absent direct effect of family economic resources on child development after controlling for potential mediating mechanisms. The study also identifies key mediating factors (e.g. maternal depression, a cognitively stimulating home environment, parenting practices and length of breastfeeding) that could be targeted by government initiatives in order to effectively improve children's intellectual development and behaviour beyond what income redistribution can achieve.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".