Pasojat e luftërave habsburge – osmane në strukturën demografike të Kosovës / The aftermath of the Habsburg-Ottoman wars in the demographic structure of Kosovo
Bibliographic record
Abstract
This paper focuses on the development and consequences of the Habsburgs - Ottoman wars in today’s Kosovo and the other ethnic Albanian areas of Sandžak, as well as of today’s Macedonia, at the turn of the XVII century and in the first four decades of the eighteenth century. This study highlights the role of Albanians in these wars, and in particular, the extremely serious consequences that these hostilities had on the majority of Albanian population inhabiting these areas. Indeed, Ottoman sources that were previously unknown to the Albanian historiography and beyond, have shed fresh new light on the circumstances moulded in those areas, at the time of the subversion of the Habsburg forces and their allies during the last quarter of 1689. They shed first-hand light, particularly on the demographic discrepancies and the massive displacement, of the Albanian Muslim population from today’s Kosovo at that particular time. These sources express very plainly the enormous depopulation of ethnic Albanian majority in today’s Kosovo and surrounding areas all through these conflicts, as a result of displacements, murder, death from starvation, disease and eventually plague epidemics, which at that time ultimately annihilated almost two thirds of the Albanian population of today’s Kosovo.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".