Elite economic forecasts, economic news, mass economic expectations, and voting intentions in great britain
Bibliographic record
Abstract
Abstract In order to test the notion that the electorate relies, derivatively, on professional economic forecasts, we consider the entire chain between elite economic expectations, economic news, mass economic expectations, and voter preferences. We find that while elite expectations are based on the objective economy, they are politically biased in the neighborhood of elections. Reports of economic news, while based on the objective economy and on elite expectations, have their own political rhythm in the form of election–related cycles. The pattern in news coverage, in turn, is mirrored by election–related cycles in personal and general expectations formed by the mass public. While the relevance of each of the linkages from elite expectations to news coverage to mass expectations is thus confirmed, our findings challenge the view that the link between mass expectations and voting intentions can be attributed mainly to the dissemination of elite forecasts to the general public. We conclude by discussing the implications of our findings for an understanding of the ability and functioning of mass electorates.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.005 | 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".