Bibliographic record
Abstract
One mechanism a group of individuals may use to select an alternative from a set of many alternatives is plurality rule: each individual votes for a single alternative, and the winner is the alternative that receives the most votes (or the set of alternatives that receive the most votes, in the case of a tie). If voting is costless, each individual's voting for her least-favored alternative is dominated, but voting for any other alternative is not dominated. An equilibrium exists in which no individual's vote is weakly dominated. If the set of alternatives is an interval of numbers and the individuals' payoff functions are strictly concave, in an equilibrium at most two alternatives tie for winner; every alternative is possible in an equilibrium. In a simple model of "divided majority" with three alternatives, a majority of individuals rank alternatives a and b above c, but disagree about whether a is better or worse than b. In a model in which each individual knows her own preferences and has probabilistic beliefs about the other individuals' preferences, whether in equilibria in a large population the majority succeeds in coordinating to defeat c depends on the precise nature of the uncertainty.
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.
How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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; both teacher heads agree on what is shown here.
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".