Legal Documents as Means of Financial Abstraction: How Bankers’ Lawyers Constructed Swaps and Changed Finance
Bibliographic record
Abstract
Abstract Finance rests on a process of abstraction, based on various material devices that have been studied by economic sociologists in recent years. The fact that many of those devices are legal in nature has not attracted much attention, even though financial instruments are typically embodied in legal documents. This paper argues that interactions involving legal documents shape both financial markets and their regulation, by specifying the contextual elements that will be deemed relevant in interpreting financial commitments. It takes as a case study the emergence of swaps since the 1980s. Through their work in standardizing, commenting, and litigating swaps contracts, bankers’ lawyers were able to recast obligations between banks and their clients in more abstract terms, discarding all references to specific business projects. Such abstraction simultaneously allowed the spectacular development of swaps markets, their positioning on the fringes of regulations, and the strengthening of bankers’ prerogatives against their clients.
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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 | 0.023 | 0.057 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.012 | 0.040 |
| Scholarly communication | 0.017 | 0.016 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 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".