Medieval Whalers in the Netherlands and Flanders: Zooarchaeological Analysis of Medieval Cetacean Remains
Bibliographic record
Abstract
Medieval historical sources suggest that cetacean exploitation was, for large parts of Europe, restricted to the social elite. This appears to have also been the case for the Netherlands and Flanders. It remains unclear, however, how frequently active hunting was undertaken, and which species were targeted. Zooarchaeological cetacean remains are often recovered from Medieval (AD 400-1600) sites in the Netherlands and Flanders, however the majority of these specimens have not been identified to the species level, leaving a substantial gap in our knowledge of past cetacean exploitation. By applying ZooMS, as well as morphological and osteometric analyses, these zooarchaeological specimens were identified to the species level. This analysis revealed that the North Atlantic right whale (Eubalaena glacialis), sperm whale (Physeter macrocephalus), and grey whale (Eschrichtius robustus) were frequently exploited. Active whaling appears to have been undertaken as well, especially in Flanders and in Frisia (the northern part of the Netherlands). Zooarchaeological cetacean remains appear to be present with relative frequency at high-status sites such as castles, as well as ecclesiastical sites, confirming the historical evidence that the social elite indeed did have a taste for cetacean meat. However, cetacean products were also available outside of elite and ecclesiastical contexts.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".