Understanding technological change in global finance through infrastructures
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Amid escalating claims about the promises and perils of emergent financial technologies (fintech), critical investigation of the extent to which specific technological changes in global finance are truly ‘disruptive’ is sorely needed. Yet, IPE has engaged little with the growing focus on fintech in popular and regulatory debates, as well as in Social Studies of Finance (SSF). This article and accompanying special issue foreground ‘infrastructures’ as a heuristic for injecting nuance into debates on the emergence, limits and implications of technological changes in global finance while bringing IPE into conversation with perspectives on fintech in cognate literatures. Building on insights developed in Science and Technology Studies (STS), we argue that tracing the ways in which infrastructures enabling financial markets to operate are assembled out of multiple old and new socio-technical devices offers productive avenues for addressing key questions arising from several entanglements underpinning technological change. The findings of contributions to this special issue are linked to two key themes in debates on the impacts of technological change: financial inclusion and financial stability. Further avenues are proposed for examining the infrastructures in which technological change occurs in global finance and beyond, while fostering on-going dialogues between IPE, STS and SSF.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it