Subjects, citizens and others: the handling of ethnic differences in the British and the Habsburg Empires (late nineteenth and early twentieth century)
Bibliographic record
Abstract
This article focuses on the role of ethnic inclusions and exclusions in administering citizenship and nationality within the British and the Habsburg Empires. The analysis discerns three ways of dealing with ethnically heterogenous populations. One follows the nation-state model and aims for internal ethnic homogeneity and legal equality. This model coined developments in Canada and Hungary. The second obeys an imperialistic pattern and implements legal discrimination between different ethnic groups. It played a decisive role in East Africa and in Bosnia to a certain degree. The third model follows a statist logic and enforces either supra-ethnic neutrality or a politics of recognition. It was most influential in Austria and India. In the British as well as in the Habsburg context ethnic differences gained significance around 1900. This ethnicising of law and administrative practice produced different results, though, in both cases, mainly due to the empires' divergent political structures. Whereas within the Habsburg Empire the three models were juxtaposed, British law and administration came to be dominated by the imperialistic pattern of ethnic discrimination against ‘non-white’ subjects. Thus, the customary distinction between a politically inclusive nationalism in Western Europe and an ethnically exclusive one in the continent's Eastern half – sometimes linked with the difference between ius soli and ius sanguinis – cannot be upheld.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.017 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".