Richard Mackenney, <i>Venice as the Polity of Mercy: Guilds, Confraternities, and the Social Order, c. 1250–c. 1650</i>. Toronto Italian Studies. Toronto, Buffalo, and London: University of Toronto Press, 2019, xiii, 471.
Bibliographic record
Abstract
Shakespeare is well known to have set two of his plays in and around Venice: The Merchant of Venice (1596) and The Tragedy of Othello, the Moor of Venice (1603). The first is often remembered for its famous speech about “the quality of mercy,” delivered by the female lead Portia in the disguise of a legal scholar from the university town of Padua. The speech helps to spare the life of her new husband’s friend and financial backer against the claims of the Jewish moneylender Shylock. The play has raised questions for Shakespearean scholars about the choice of Venice as an open city where merchants of all nations and faiths would meet on the Rialto while the city’s Senate, composed of leading merchants, worked hard to keep it open to all and especially profitable for its merchants. Those who would like to learn more about the city’s development as a center of trade can learn much from Richard Mackenney’s new book.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.007 | 0.016 |
| Scholarly communication | 0.008 | 0.015 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.009 | 0.007 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".