Capitalists, managers, professionals and mortality: Findings from the Barcelona Social Class and All Cause Mortality Longitudinal Study
Bibliographic record
Abstract
AIMS: To examine the effects of Neo-Marxian social class (i.e. measured as relations of control over productive assets) and potential mediators such as labour-market position, work organization, material deprivation and health behaviours upon mortality in Barcelona, Spain. METHODS: Longitudinal data from the Barcelona 2000 Health Interview Survey (n = 7526) with follow-up interviews through the municipal census in 2008 (95.97% response rate) were used. Using data on relations of property, organizational power, and education, social classes were grouped according to Wright's scheme: capitalists, petit bourgeoisie, managers, supervisors, and skilled, semi-skilled and unskilled workers. RESULTS: Social class, measured as relations of control over productive assets, is an important predictor of mortality among working-class positions for men but not for women. Workers (hazard ratio 1.60, 95% confidence interval 1.10-2.35), managers and small employers had a higher risk of death than capitalists. CONCLUSIONS: The extensive use of conventional gradient measures of social stratification has neglected sociological measurements of social class conceptualized as relations of control over productive assets. This concept is capable of explaining how social inequalities are generated. To confirm the protective effect of the capitalist class position and the ''contradictory class location hypothesis'', additional efforts are needed to properly measure class among low-level supervisors, capitalists, managers, and small employers.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".