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
Abstract If voters are asked to vote twice on the same issue in a single year, why might they initially reject the proposal but then vote to approve it the second time? This has happened three times in EU referendums (Denmark on the Maastricht Treaty in 1992–93 and Ireland on the Nice Treaty in 2001–02 and the Lisbon Treaty in 2008–09). No work has yet compared all six of these referendum campaigns. I focus on the campaign strategies of the Yes and No sides and investigate whether campaigners act differently in the second campaigns. Based on fieldwork in Denmark and Ireland, 38 in‐depth interviews with campaigners and public opinion data, I show that the Yes campaigners learned from their mistakes and changed their campaign strategies in the second rounds. Not only did they secure guarantees from the EU to neutralize the No side's arguments; they also used more emotional campaign arguments in the second campaigns.
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 | 0.016 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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