Bibliographic record
Abstract
Do housing prices influence how individuals perceive their economic standing? Recent research linking housing prices to electoral outcomes suggests that they do. The theoretical expectation is that individuals update their economic perceptions based on housing costs and vote accordingly. However, it remains empirically untested whether housing prices trigger an economic reaction, and if so, whether this pertains to individual economic standing or sociotropic ones such as the national economy or the level of inequality. Testing this expectation is essential since other theoretical paths could explain the assumed link between housing prices and political reactions. This paper interrogates this key assumption by testing whether renters and owners react differently to housing market information. In two experiments conducted in the United States and Canada, treatments inform participants about local housing costs. Informing respondents about the cost of home ownership in their locality triggers economic anxiety among renters, but not all homeowners since only economically at-risk owners exhibit attitudes akin to renters. The results are important for our understanding of the political consequences of surging housing prices and its potential link with anti-establishment vote. The study shed light on the economic anxiety this may generate and identify the groups most affected.
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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 | 0.001 | 0.004 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".