Managing Diversity through Non-Territorial Autonomy:\nAssessing Advantages, Deficiencies and Risks\nTove H. Malloy, Alexander Osipov, & Balázs Vizi (Eds.)\nOxford University Press, 2015, 336 pages
Why this work is in the frame
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Bibliographic record
Abstract
The book -meant to be the first volume within a broader research project -explores the notions of non-territorial autonomy both by exploring the concept itself and by presenting different case studies from Europe and North America.Its ambition was to fill the gap in social sciences, in which much larger attention was given to the concept of territorial autonomy (TA), whereas forms of non-territorial autonomy (NTA) were inadequately explored, defined and evaluated.The main part of the book is divided into three parts, each presenting case studies corresponding to different forms of non-territorial autonomy: voice, quasi-voice and non-voice.While voice regards the self-governing policies for ethnocultural minorities, quasi-voice regards self-management minority institutions established under public and private law in order to help minorities preserve their culture, while non-voice pertains to symbolic policies without meaningful ethno-cultural autonomy.The first part of the book, presenting cases of voice, contains case studies of nonterritorial minority arrangements in Hungary, Croatia, Serbia and Slovenia, as well as the case of Sami parliaments in Finland, Norway and Sweden.The second part of the book, dedicated to examples of quasi-voice, presents the cases of minority educational self-management in Canada, institutions of autonomy for Sorbian people in Germany
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it