Federalism. Theory and Neo-Functionalism: Elements for an analytical framework
Bibliographic record
Abstract
The purpose of this article is to propose a draft for an analytical frame for analyzing regional integration consisting of federalism theory and neo-functionalism. It starts out discussing the concept of regional integration setting up a stagiest model for categorizing it.Then follows an analysis of federalism theory and neo-functionalism. One argument of this article is to understand federalism theory as a regional integration theory. Another is to<br/>look at federalism theory as complementary to neo-functionalism when trying to explain regional integration. Federalism theory, in an extended Riker-McKayian way, is able to explain the cases of ‘big bang’ integration (USA, Australia, Canada), but not an ‘organic’ integration process. Neo-functionalism, on the other hand, is not able to explain this relatively fast form of integration, but it is – in its new version - able to analyze and explain the ‘organic’ or slow integration processes like those happening in Europe, and other places in the world. Thus the two should be seen as complementary and they are, jointly, a<br/>frame catching most processes of regional integration.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".