Bibliographic record
Abstract
A framework for analysis 1. An introduction to multi-level electoral competition - Charlie Jeffery and Dan Hough 2. Party organisation in multi-level contexts - Ingrid van Biezen and Jonathan Hopkin 3. Party systems in multi-level contexts - Lori Thorlaksson Case studies 4. Disconnected competition in Canada - Steven Wolinetz and Ken Carty 5. Multi-level party competition and co-ordination in Belgium - Lieven de Winter 6. Multi-level electoral competition: sub-state elections and party systems in Spain - Francesc Pallares and Michael Keating 7. Germany: an erosion of federal-Lander linkages? - Dan Hough and Charlie Jeffery 8. Regional elections in Italy: national tests or regional affirmation? - John Loughlin and Silvia Bolgherini 9. Austria: divergence within limits - Alan Siaroff and Amir Abedi Multi-level electoral competition in the UK 10. Devolution and electoral politics in Wales - Richard Wyn Jones and Roger Scully 11. Devolution and electoral politics in Scotland - Catherine Bromley 12. British political parties and devolution: sdapting to multi-level politics in Scotland and Wales - Jonathan Bradbury 13. Devolution and electoral politics: where does the UK fit in? - Charlie Jeffery and Dan Hough
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.020 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".