<scp>The Salient Issue of Issue Salience</scp>
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 This paper proposes a model where the set of issues that are decisive in an election (i.e., the set of salient issues) is endogenous. The model takes into account a key feature of the policy‐making process, namely, that the decision‐maker faces time and budget constraints that prevent him from addressing all of the issues that are on the agenda. We show that this feature creates a rationale for a policy‐motivated decision‐maker to manipulate his policy choice in order to influence which issues will be salient in the next election. We identify three motivations for the decision‐maker to manipulate his policy choice for salience purposes. One is to make salient an issue on which he has an electoral advantage. A second motivation is to defuse the salience of an issue on which he is electorally weak, which is accomplished by either implicitly committing to a policy outcome or triggering a change of salient issue for the challenger. A third motivation is to induce the opposition party to nominate a candidate who, if elected, will implement a policy that the incumbent decision maker finds more palatable.
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 | 0.005 | 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 | 0.000 | 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