Climbing up a Steeper Staircase: Intergenerational Social Mobility across Birth Cohorts in Argentina
Bibliographic record
Abstract
Argentina is a middle-income developing country that has undergone significant economic change in the last quarter of the 20th century. Many studies address the impact of market oriented policies on the labor market (e.g., the expansion of precarious work, the increase in poverty and income inequality); however, there have been few empirical studies that analyze changes in the degree of openness in class structure. Recent studies on social stratification in industrial societies show that change in opportunities for mobility almost always goes from less to more open, even though inequality has increased in most of these countries over the last 30 years. This paper introduces Argentina to this kind of analysis to explore how and to what degree opportunities for social mobility have changed at the beginning of the 21st Century across birth cohorts. Particularly, the study focuses on the relative odds of upward mobility over time for persons who come from working class origins. Data sources include six National Social Mobility Surveys from 2003 to 2010, Gino Germani Institute-UBA. Rates of mobility, logistic regressions and log-linear models are applied to the task of modeling changing openness in social mobility in Argentina.The analysis shows that for men and women occupational change has opened structural opportunities to upward mobility. In comparison with other countries of Latin America and Europe, Argentina is (in fact) a quite open society. The rates of upward mobility from working class origins to the middle classes are high thanks to the expansion of high-skill service occupations. However,younger birth cohorts of working classorigins have had less long distance upward mobility andgreatershort-distance mobilityto the routine non-manual class.The growth of structural occupational opportunities in professional and managerial positions does not change class barriers. Social fluidity results show a general trend of persistent inequality in class mobility over time, and if change has happened, it has been in the direction of a decrease in social fluidity.Further analyses provide evidence of aslight wideningin the gap between the upper middle classes and the working class with regard to opportunities of upward mobility.It seems that sons and daughters of working class families areclimbing a steeper stairway because class barriers in the upper middle classes have increased.This study could be interpreted as a key case to understand that public policy is decisive for creating greater openness and equality of opportunity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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; both teacher heads agree on what is shown here.
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".