Bibliographic record
Abstract
Both of the main concepts underlying the analysis in this volume - ‘multilevel governance’ and ‘democracy’ — could be described as complex and essentially contested. 1 Exploring their interaction opens up even greater possibilities for debate and disagreement. In spite of its varying and sometimes ambiguous meanings, the concept of governance has gained increasing prominence in recent years, in large part reflecting the transition from state-centric governing relationships that marked the post-Second World War Western nation state to a greatly more complex constellation in which states and their governments are but one important group of players among various layers and centres of political power. 2 As J. Pierre points out, two main thrusts have driven the development of the governance concept. The first involves ‘to what extent the state has the political and institutional capacity to “steer” and how the role of the state relates to the interests of other influential actors’. The second thrust, less state-centred, concerns the process of coordination and self-governance within networks and partnerships, involving both public and private actors. 3 The multilevel factor adds an additional layer of abstraction and complexity. But the transformation of governing relationships in recent decades implies that it is no longer possible to focus on a single level of analysis (the international, national, or subnational), since these layers are interconnected in multiple ways. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.414 | 0.233 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".