Who are the champions? Inequality, economic freedom and the Olympics
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
Abstract Does inequality affect outcomes? To answer, we use the microcosm of Olympic competitions by asking whether a country's level of inequality diminishes its performance. If it does, is it conditional on institutional factors? We argue that the ability of economically free societies to win medals will not be affected by inequality. In these societies, institutions generate incentives to invest in the talents of individuals at the bottom of the income distribution (potential athletes otherwise constrained in the ability to expend resources on training). These effects mitigate those of inequality. The incentives that promote investments in skills across the income distribution are weaker in unfree societies and they cannot mitigate the effects of inequality. Using the Olympics of 2016 in combination with the Economic Freedom data, we find that inequality only matters in determining medal numbers for unfree countries. We link these results to inequality and its effects on economic outcomes.
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.
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 | 0.002 | 0.001 |
| 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