Bibliographic record
Abstract
Probate inventories are listings of property that were sometimes taken upon an individual's death. A team of appraisers would tour the home and lands of the deceased, describing everything of value and assigning an estimated worth. This appraisal would help the administrator or executor of the estate pay off all creditors, with the remainder being distributed according to a will or divided among heirs for those who died intestate. For the past four decades family historians as well as economic and social historians have made extensive use of these inventories, but it is hard to make generalizations about them, as laws governing them vary according to the jurisdiction and year being examined; the literature on probate inventories is consequently very wide-ranging. Used initially for the study of wealth distribution, researchers have also used them to investigate other areas of historical interest. For example, doctors' kits and libraries inform us about the material culture of medicine; word usage and spelling in the lists interest linguists as well as intellectual historians, who also find an indication of the degree of literacy in the number of documents signed by "x" rather than a name; in named books and ownership of Bibles there is evidence of learning and intellectual interests; pottery, dishware, and utensils interest archaeologists; sociologists find status symbols in the details of furnishings, apparel, and cultural objects; agricultural implements tell of farming methods and crop specialization; horses, harness, wagons, and boats indicate modes of production as well as travel; tools speak of craftsmanship; household implements like spinning wheels, wool cards, looms, and soap kettles suggest household production. We can also examine patterns such as the seasonal round of work and the sexual division of labor.
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 | 0.045 | 0.199 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.016 | 0.017 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.017 | 0.040 |
| Open science | 0.005 | 0.012 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.176 | 0.089 |
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".