Bibliographic record
Abstract
A gap persists in understanding how norms of business conduct and behaviours have developed to the point where end-results are valued above duty of care to others. Profitable outcomes are used to justify failures to uphold virtues such as honesty, integrity and compassion for others. The ramifications of continuing to foster these business habits reach well beyond worldwide financial crises and economic disruption – they affect how we live together and our capacity to sustain a healthy environment for all. My search for genealogical traces of the “ethics problem” in contemporary business practices led to the early modern period, a time that predates England’s formal financial institutions, stock exchanges and state-driven economic policies. This dissertation investigates two forms of Jacobean performance, the annual Lord Mayor’s Show in the City of London and commercial plays staged contemporaneously, as evidence of shared ideas and beliefs that shaped business identity, accepted standards of conduct and market development. My research is structured as three case study pairings of a civic show and a commercial play. The first case brings together Anthony Munday’s show Chruso-thriambos (1611) and Thomas Middleton’s play A Chaste Maid in Cheapside (c. 1611-1613) to focus on creditors and money-makers linked to the Goldsmiths’ Company. The second looks to aspiring leaders and entrepreneurs through an analysis of the Merchant Taylors’ Company sponsored show Monuments of Honor (1624), written by John Webster, and Ben Jonson’s The Staple of News (1626). The third study examines global ventures through Thomas Middleton’s The Tryumphs of Honor and Industry (1617) prepared for the Grocers’ Company and John Fletcher’s The Island Princess (c. 1619–1621). The juxtaposition of two forms of theatrical performance, with seemingly different motivations and perspectives, reveals normative ideas about how business agents were expected to act and how successful performance as a business agent was recognized and measured. Performances centred on business stories demonstrate that by the Jacobean period there was already an established and naturalized expectation that business agents would prioritize teleological – end result, outcome-oriented – goals above pursuit of virtuous ideals or fulfilment of duty to other agents. Success was measured by an accumulation of signs of material wealth that was accepted as indicator of an inherent worth deserving of social recognition.
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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 | 0.009 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.034 |
| Scholarly communication | 0.016 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".