From EURATOM to “Complex Systems”: Technology and European Government
Bibliographic record
Abstract
In a recent series of papers written for the European Commission's Cellule de Prospective (CdP), Notis Lebessis and others have begun to think about the European Union - its political future, its accomplishments, and the challenges facing it - in terms of a social condition they define as complexity. In brief, the CdP suggests that the EU represents a peculiarly inventive and functional response to the increasingly complex environment within which modern government must operate. As social and economic life has become more complex, the CdP argues, the forms of network organization associated with the European Union have become more and more relevant. challenges presented by contemporary society in terms of complexity, diversity and interdependency mean that these traditional forms [e.g., national parliamentary politics] are stretched beyond their limits and that new forms begin to emerge.1 At the same time, knowledge has acquired a particular centrality to the constitution of the contemporary European system of government. The role of the public authorities is to escape from the constraints of the institutional (bureaucrat/ expert) construction of problems and solutions.2 The task of the EU is to encourage participation and to foster an economy based on collective learning. The conclusion is intended to be both descriptive and normative. The CdP's reports both account for the development of the EU in the past and provide blueprints for the future. Their publication (both internally and on the internet) is intended to be much more than an analysis of EU government - to be, indeed, a significant political event itself.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.029 |
| Scholarly communication | 0.012 | 0.015 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.006 | 0.005 |
| 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; 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".