Bibliographic record
Abstract
This list (except for the rightmost column) is compiled and transcribed from a summary of the (original) Heyrick (1694) document, which is stored in the archives of the British Library and confirmed against the updated Heyrick (1695) list. The 1695 document is part of the collection of the Institute and Faculty of Actuaries (which is also the cover image of the book). The number of years lived, in which (only) a lower bound is provided is based on the King (1730) surviving nominee list and the Anonymous (1749) surviving nominee list, which are both available in the British Library. The nominees listed with an exact number of years lived is based on (i.) the assumption that their deaths were recorded in chronological order in the final page of the King (1730) list, and (ii.) the number of nominees who died in every year is based on the JHC (1803) document. Presumably, Finlaison (1829) himself had access to the exact death dates of all the nominees on this list, since he compiled one of the earliest English mortality (and life expectancy) tables based on this tontine. Alas, I haven't been able to locate the Finlaison “list,” but I would love to get my hands on it.
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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.409 | 0.321 |
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".