Bibliographic record
Abstract
This dataset, which accompanies the public website hertogdombrabant.nl, contains several GIS files associated with the medieval Duchy of Brabant. These files have been adapted to correspond with the hearth censuses and fiscal repartitions collected by myself and Arend-Elias Oostindiër. The polygon GIS is an abridged adaptation of the 'Historical Atlas of the Low Countries' (v7), which can be downloaded in full here. The localities GIS contains a substantial summary of the fiscal data that can be downloaded in the links above, and is specially prepared for users not familiar with creating spatial joins. The cartogram GIS was created using ScapeToad. It is a collection of hexagons, each hexagon representing an equal share in the census or fiscal repartition. The boundaries GIS contains the borders of the Brabantine quarters, both in 1374 and 1437. Two special additions are the GIS layer of all religious institutions within Brabant, as well as a few religious institutions outside the duchy that contributed in the ducal aids. The dataset combines the total population living within the walls of the institutions in 1526 (including professed and non-professed members, lay persons, secular priests, and personnel), and information on the institutes participation in the Estates and/or contribution to the ducal taxes. Please note that each administrative quarter interpreted the 1526 census slightly differently. Two examples make this clear. Whereas refuge houses are included in the quarter of Louvain, they are absent elsewhere. The quarter of 's-Hertogenbosch does include much more detailed information on hospices than the other quarters. More regular monastic convents are included in all four quarters. Last but not least, the dataset includes a complete list of towns, noblemen, and prelates listed in the convocation of 1406. This list was created together with Dr. Mario Damen, based on a pre-existing edition and justification by Mario Damen which can be found here. It includes, when possible, the suspected place of origin of the person mentioned in the convocation lists. In many cases, only the bailiwick or quarter could be identified. In those cases, the person is listed in the capital of the bailiwick or quarter. This is clearly marked in the dataset. All files are coupled with a QGIS symbology file, which provides the user with an example of how the GIS layers can be visualised.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.192 | 0.138 |
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".