Analysis of the Increasing Income Gap between the Rich and Everyone Else
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
The growing disparity in income between the rich and middle/lower income groups has resulted in significant skewness in the distribution of wealth in the U.S. The short and tall of it is that the real incomes of the top .01 percent of Americans rose seven fold between 1980 and 2007, but the real income of the median family rose only 22 percent, less than a third of its growth over the previous 27 years. Two main reasons given by economists are technological innovation and inadequate technical education in the U.S. However, there are several other factors that are relevant. This paper analyzes the other issues: 1) the funding of federal political campaigns, 2) the effects of offshoring, 3) the role of the U.S. tax code, and 4) the absence of a strong connection between performance and rewards that may be related to the recent shift in wealth. While wage differences naturally occur in a capitalistic system, massive differences provoke social unrest and the rise of demigods advocating collectivist solutions.
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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 | 0.000 | 0.000 |
| 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