The influence of childhood IQ and education on social mobility in the Newcastle Thousand Families birth cohort
Bibliographic record
Abstract
BACKGROUND: It has been suggested that social, educational, cultural and physical factors in childhood and early adulthood may influence the chances and direction of social mobility, the movement of an individual between social classes over his/her life-course. This study examined the association of such factors with intra-generational and inter-generational social mobility within the Newcastle Thousand Families 1947 birth cohort. METHODS: Multivariable logistic regression was used to examine the potential association of sex, housing conditions at age 5 years, childhood IQ, achieved education level, adult height and adverse events in early childhood with upward and downward social mobility. RESULTS: Childhood IQ and achieved education level were significantly and independently associated with upward mobility between the ages of 5 and 49-51 years. Only education was significantly associated (positively) with upward social mobility between 5 and 25 years, and only childhood IQ (again positively) with upward social mobility between 25 and 49-51 years. Childhood IQ was significantly negatively associated with downward social mobility. Adult height, childhood housing conditions, adverse events in childhood and sex were not significant determinants of upward or downward social mobility in this cohort. CONCLUSIONS: As upward social mobility has been associated with better health as well as more general benefits to society, supportive measures to improve childhood circumstances that could result in increased IQ and educational attainment may have long-term population health and wellbeing benefits.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".