Exactly How Has Income Inequality Changed?
Bibliographic record
Abstract
The recent resurgence of income inequality in some of the core societies has spawned a wide-ranging debate as to the culprits. Progress in this debate has been complicated by the fact that many of the theories that have been developed to account for the inequality upswing imply radically different patterns of distributional change, while predicting the same outcome in terms of the behavior of standard summary measures (e.g. a rise in the Gini coefficient or in Theil’s inequality). Handcock and Morris (1999) have developed methods that allow the analyst to precisely identify patterns of distributional change and a set of summary measures to characterize such changes. These are based on the relative distribution, defined for our purposes as the ratio of the fraction of households in the baseline year to the fraction of households in the comparison year in each decile of the distribution of income. We use the available high-quality data from the Luxemburg Income Study to explore the evolution of household income inequality in 16 core societies. We describe exactly how inequality grew in some core societies since the late 1960s and discuss the extent to which patterns of distributional change were homogeneous or heterogeneous across the core. We find that: 1) rising inequality is generally associated with polarization, rather than upgrading or downgrading alone; 2) among those societies experiencing the largest increases in inequality, upgrading typically takes precedence over downgrading in the course of such polarization; and 3) declining inequality, where it occurs, has been the result of convergence, with the magnitude of the shift from the lower tail to the middle exceeding that of the shift from upper tail to the middle.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.005 | 0.009 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".