Bibliographic record
Abstract
The purpose of the article is to describe the main characteristics of the financingof sub-central bodies in federal states. The article focuses chiefly onbodies of an intermediate level, that is, the states that form the federation.The analysis is based on the experience of Germany, Australia, Austria, Canada,Switzerland and the USA. At the same time, the article makes referencesthroughout to the financing of the [Spanish] Autonomous Communities todetermine whether this is in line with the sub-central financing of thosecountries analysed. Finally, it also highlights the manner in which the modelof financing in the new Catalan Statute of Autonomy brings us closer to thecharacteristics of a federal model. The article’s analysis proceeds through theassessment of a series of underlying issues: the degree of decentralizationin federal states, both with reference to expenses and income from taxation;expense functions by levels of government; income structure in governmentsof an intermediate level, highlighting the degree of financial dependence;the tributary power and assignation of taxes at a sub-central level; the subsidiesof taxation levelling, and finally the political-institutional mechanismsof coordination between the various levels of government.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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 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".