Class, partisanship and the great recession: the conflicting influences on attitudes towards inequality during economic crises
Bibliographic record
Abstract
While some scholars suggest that critical attitudes towards inequality follow the class gradient during recessions, others find that classes are largely unresponsive. In this article, I consider how party affiliation interacts with class to shape perceptions of inequality during a recession. I argue that it is important to look at the interplay between class and partisanship to better understand individual views towards inequality during times of economic crises. Leveraging data from the International Social Survey Programme before and after The Great Recession, I find that the recession did not raise awareness of inequality across classes. This is because party affiliation moderates the relationship differently according to class. Specifically, party affiliation is more important in shaping the inequality views for the upper class and less so for the working class. Future research needs to consider the interplay between class and politics when exploring how inequality attitudes respond to economic crises.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.004 |
| 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".