Charity and the Economy of Power: The Ospedale di Santa Maria della Scala and Siena's Network of Charity in the Sixteenth Century
Bibliographic record
Abstract
This study examines charitable institutions as a source of power through an analysis of Siena’s largest and most prominent hospital, the Ospedale di Santa Maria della Scala. This analysis is accomplished by situating Santa Maria della Scala in the context of relationships between Siena and its surrounding territory before and after Siena’s loss of independence in 1555. From its eleventh century origins, Santa Maria della Scala developed social, religious, and political power within Siena, serving as the city’s central source of charity and playing a key role in civic rituals and devotions. Additionally, through its vast network of farms and small hospitals, Santa Maria della Scala exercised economic power and influence across the Sienese state. Through the early sixteenth century, Siena’s government drew as needed on the social, religious, and economic power of the hospital to reinforce ties with both the urban population and subject communities. However, internal political strife, increasing foreign involvement in local affairs, and a war at mid-century upset the distribution of power and strained relations between Santa Maria della Scala and the city government. After Siena’s loss of independence in 1557 and subsequent governance by Cosimo de’ Medici, competition for control of the hospital between local elite and the Medici of Florence resulted in a process of negotiation which demonstrates the ability of hospitals to function simultaneously as local power centres and as arms of the territorial state. Thus, an analysis of Santa Maria della Scala and Siena in the sixteenth century not only highlights the complex power dynamics that comprised the Grand Duchy of Tuscany, but also contributes to debates surrounding the transition in Italy from medieval communes to early modern states, and the distribution of power within those states.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.021 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".