Changing Income Inequality in the Second Half of the 20th Century Preliminary Findings and Propositions for Explanations
Why this work is in the frame
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Bibliographic record
Abstract
There exists a rather widespread professional consensus that income inequality both within and between societies in the world system has increased over the last quarter of a century. This, however, does not represent a secular trend since inequality between WWII and the 1970s was rather stable or decreasing. For the increasing inequality both within and between societies since the 1970s we present fresh evidence which helps to settle open questions of previous research. Less consensus has been achieved until now with regard to explanations. Arguing that monocausal explanatory schemes are of little help, the paper suggests eight propositions for an explanation. The evaluation of them is also enriched by diverse pieces of preliminary empirical evidence. The paper also brie?y considers which factors are responsible for a rather transitory increase and those which suggest a lasting higher level of inequality in the world.
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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 | 0.013 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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