Consumer markets and national income inequality: A study of 18 advanced capitalist countries
Bibliographic record
Abstract
Sociologists have paid scant attention to the possibility that the structure of the macro-economy is an important determinant of income inequality. Although prior research finds negative links between the size of the public sector and income inequality, no study to date considers whether the size of consumer markets has distributional consequences as well. To investigate this possibility, the present study measures the size of national consumer markets with the System of National Accounts used by governments to calculate gross domestic product (GDP). Based on data from 18 advanced capitalist countries over nearly a 40-year period, two-way random effects regression models reveal a strong and positive link between the size of consumer markets and income inequality. This finding is robust to the inclusion of numerous control variables, and to the consideration of endogeneity within the causal relationship. The proposed theoretical explanation centers on ideas developed by Polanyi, and suggests that economic activity in consumer markets creates higher levels of individual differentiation, and hence higher levels of income inequality, than economic activity in other sectors of the economy. The study concludes by highlighting ways future research can advance our theoretical and empirical understanding of this topic.
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How this classification was reachedexpand
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 | 0.003 | 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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".