The Subsidiarity Arrangement of Global Governance and Sustainable Development
Bibliographic record
Abstract
In the post-Cold War realm of international relations, the United Nations is "overheating," overburdened by the demands of their expanded operations, in part due to its massive expansion of membership since conception, which has grown to include several developing nations. Specifically, in the realm of international sustainable development, this expansion has drastically increased the scope of UN objectives responsibilities. What we learned from the period of the 1990s, is that the “Washington Consensus” series of macroeconomic policy recommendations anchored around the mantra “stabilize, privatize, and liberalize,” which had failed to adequately instill sustainable long-term growth in Sub-Saharan African, is that this narrow field of market-oriented reforms could not uniformly solve issues of development across the world. Attempts to copy-paste policy reforms from one country often failed, and precisely this observation entails the application of subsidiarity. This paper employs a qualitative methodology to investigate the potential role of a subsidiarity arrangement in easing the burden on the UN system, through a global division of labour across local, regional, and international levels of governance, in studying sustainable development and poverty eradication efforts in sub-Saharan Africa.
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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.014 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".