Bibliographic record
Abstract
In this article, I will engage the contested terrain of contemporary (online) transparency by looking at it through the lens of a “cultural studies of finance.” I will focus here especially on the conflicting but complementary tactics of technologically enhanced transparency and how it is being strategically mobilized by, on the one hand, an increasingly vocal macroeconomically informed and invested online community of bloggers and online activists (“econo-bloggers”) and, on the other hand, by one of the primary targets of their transparency-seeking attacks: the Federal Reserve (the Fed)—the central bank of the United States. I want to show how the transparency tactics being pursued by both parties at once conflict with and complement one another as both parties play the transparency game with the same objective: to win the monetary policy debate and thereby achieve a sort of monetarily significant ontological legitimacy. This legitimacy is premised upon a monopolization of the very nature of monetary “truth”: a form of truth that’s becoming increasingly important to control and manage in light of, for instance, recent economic catastrophes, the faith-based nature of contemporary credit- and fiat-based money, and ever-inflating commodity costs (e.g., gold and oil). But while both the econo-blogosphere and the Fed champion transparency-promoting agendas, their allegedly transparency-promoting tactics are not so much about getting at “objective” realities concerning money as they are about controlling the message. Transparency in this online macroeconomically inflected infowar is a tool used both offensively and defensively either to maintain or subvert status quo monetary policy; more prosaically, transparency—and the appeal to transparency as a sort of moral or ethical “good”—has today become a technologically necessitated public relations tool masquerading behind a veil of authenticity and unadulterated exposure.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.085 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".