A szlavón várnemesek családi kapcsolatai és családi hálózata a 15. század végén és a 16. század elején
Bibliographic record
Abstract
The mapping of family ties and kinship networks is not an easy task given the medieval resource endowments, mainly because fewer data on noble daughters are preserved in the sources than on sons. Often we can only guess which noble families were related to each other (by female lineage) from the landed estates of a family or from scattered records of kinship. The world of the nobles at the bottom of the noble hierarchy, however, is an ideal setting for a deeper understanding of these kinship relations and networks, and of the relationships between families. The reason for this lies in their inheritance practices, which were common in their circles and differed from those of the nobility in a few respects. Among the noble families, inheritance was basically similar to that of the nobles, the estate passed from father to son/sons, and the daughter/daughters received a quarter, which is referred to in our sources as the common quarta puellaris or quarta filialis. However, the very important and significant difference between the two groups was that the daughters of noble families usually received the quarter in kind. In the event of the death of a male or female noble without leaving a legacy, the descendants, grandchildren or great-grandchildren of the daughter’s side of the family also had a claim to her property. When someone claimed a share of an estate as a female descendant, the name of his mother or grandmother was of course included in the deed to support his claim.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.158 | 0.074 |
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".