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
This article sets out to find ways of analysing the relationship of regional and statewide electoral processes in multi-level systems. First, we analyse a number of `top down' approaches with the aim of assessing how and when statewide issues are perceived as shaping regional election outcomes. Second, we discuss a `bottom up' approach in which the importance of territorial politics can be measured. Both of these approaches, although not originally developed for use in this particular context, provide at least initial techniques for mapping out the dynamics of multi-level voting. They test for the subordination of regional elections to the electoral rhythms of statewide politics as well as exploring how different patterns of voting behaviour compare from region to region and from election to election. Finally, we move on to apply these two basic models to the cases of Germany, Canada and Spain, illustrating that in contexts which lack deep territorial cleavages, regional and statewide election results are broadly similar. However, in territorially heterogeneous environments, this pattern of subordination of regional elections is broken up by territorially specific influences.
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 | 0.001 | 0.000 |
| 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