Bibliographic record
Abstract
Cultural diversity has two main roots in contemporary societies. When the plurality of cultures is linked with migration trends, we are facing multicultural societies or, to use Will Kymlicka’s words, polyethnic societies. National diversity is something else: “it arises from the incorporation of previously self-governing, territorially concentrated cultures into a single state”. However, contrary to Kymlicka, I do not think we should call all countries which contain “incorporated national cultures” “multinational states”. It overstretches the concept of “multinational state” while emptying the concept of nation-state: according to that definition, almost all countries in the world would be defined as “multinational states”, the exceptions being Iceland and the Koreas commonly cited as two countries which are made up of a homogeneous ethnonational group. The concept of “multinational state” should be used in a more restrictive way, not only in order to save it as an analytical tool, but because there are two distinct features of national plurality. The first is one where a generally unitary state contains “national minorities” i.e. groups of people which are a minority in that state but whose kin-group is a majority in a neighboring state. A typical case in Eastern Europe is the case of Romania and Slovakia which have important Magyar national minorities (linked, in various ways, with the neighboring Republic of Hungary): those states should be defined as nation-states with national minorities.The other feature of national plurality is the one where a state contains two or more nations (understood as historic/cultural communities). Only when states contain such internal nations should they be called multinational states. Examples of such internal nations are the Basque country, Catalonia and Galicia in Spain, Scotland in the UK, Flanders in Belgium, Quebec in Canada… and in the non Western World, Tatarstan, Chechnya in Russia, Tibet and the Uyghur region in China, “Kurdistan” in Iraq and many others.
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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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.029 |
| Scholarly communication | 0.014 | 0.021 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.006 | 0.015 |
| Insufficient payload (model declined to judge) | 0.007 | 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".