A Global Law of Diversity : Evolving Models and Concepts
Bibliographic record
Abstract
This book provides a global perspective on the accommodation of diversity within constitutional traditions, considering the most innovative approaches and legal instruments of the Global North and Global South. This field of study, traditionally dominated by a Global North approach based on majority-minority and rights-based discourse, is undergoing significant development. The work thus assesses the appropriateness of the existing mainstream theoretical tools and concepts – in particular minority and minority-related concepts as well as rights discourse – to grasp the ongoing evolution of this field of law. A reconsideration of the traditional conceptual categories and the introduction of the concept “Law of Diversity” is proposed as a theoretical framework to grasp the ongoing developments in this area. Among the models studied, those that are referred to as emergent models for the accommodation of diversity in the Global North appear to be particularly in need of theoretical recognition. To this end, the theory of federalism is used to serve a rather unexplored theoretical function. Federal theory is put forward as a theoretical instrument to frame and explain the emergent instruments for the accommodation of diversity, as well as provide practical solutions for their development. The book will be of interest to researchers, academics, and policy-makers working in the areas of comparative constitutional law, minority and indigenous rights law, and federal studies. The Open Access version of this book, available at http://www.taylorfrancis.com, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives (CC-BY-NC-ND) 4.0 license.
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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 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.040 |
| Scholarly communication | 0.013 | 0.022 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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".