For and Against Brexit: A Survey Experiment of the Impact of Campaign Effects on Public Attitudes toward EU Membership
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
What are the lessons of the 2016 referendum on UK membership of the European Union (EU) regarding the effects of message framing? This article reports findings from an innovative online survey experiment based on a two-wave panel design. The findings show that, despite the expectation that campaign effects are generally small for high-salience issues – such as Brexit – the potential for campaign effects was high for the pro-EU frames. This suggests that within an asymmetrical information environment – in which the arguments for one side of an issue (anti-EU) are ‘priced in’, while arguments for the other side (pro-EU) have been understated – the potential for campaign effects in a single direction are substantial. To the extent that this environment is reflected in other referendum campaigns, the potential effect of pro-EU frames may be substantial.
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.
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 | 0.004 | 0.007 |
| 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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it