The Inheritance of Employers and Nonlinearities in Intergenerational Earnings Mobility
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A growing literature addressing the intergenerational transmission of earnings often forms the backdrop for policy discussions dealing with equality of opportunity. This literature is generally framed in the context of a linear regression to the mean model, and motivated theoretically by models of parental investments in the human capital of their children as in Becker and Tomes (1986, 1979) and Loury (1981). The major concern of the empirical research has been the challenge of correctly estimating the elasticity of earnings between parents and their children in the presence of measurement errors and life cycle biases. Atkinson, Maynard, and Trinder (1983), Solon (1992, 1989) and Zimmerman (1992) offer a starting point that has led to a large number of studies from a number of countries, surveyed by d’Addio (2007), Björklund and Jäntti (2009), Black and Devereux (2011), Corak (2006), and Solon (2002, 1999). Böhlmark and Lindquist (2006), Grawe (2006), Haider and Solon (2006) and Nybom and Stuhler (2016) represent some recent methodological developments.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it