SYMPOSIUM OVERVIEW: CONCEPTUALIZING NEW GOVERNANCE ARRANGEMENTS
Bibliographic record
Abstract
This symposium, ‘Conceptualizing New Governance Arrangements', takes up the challenge of refining governance theory to better integrate work in several disciplines, most notably politics, public administration and law. To this end, we argue for a theoretical framework that profiles three key dimensions of governance: institutional, political and regulatory. This framework, in our view, offers new insights into the nature and operation of various governance arrangements, and offers the potential to assess and measure change within such arrangements over time. After describing our methodology for selecting and analysing the case studies profiled in the symposium, we introduce each of the articles that apply our three‐dimensional governance framework. These articles employ the framework to consider a variety of contemporary governance scenarios that vary widely by sector (environmental, climate change, forestry and education policy) and level of analysis (sub‐national, national, and bi‐national).
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.010 | 0.016 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.011 | 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".