Governing Finance: Global Imperatives and the Challenge of Reconciling Community Representation with Expertise
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
Abstract Although the regulation of financial institutions and global markets has been subject to extensive research and policy practice, regulation often comes second to governance: regulation cleans up failures of governance in the management and performance of private financial institutions and markets. There are two theories of the nature and practice of governance; one emphasizes its functional performance, whereas the other emphasizes its political foundations. In this article, I suggest that best practice seeks to reconcile functionalism with community representation and that representation is a virtue in its own right and need not be seen as antithetical to functional efficiency. To sustain these arguments, I note the distinctive characteristics of financial decision making under risk and uncertainty, using simple examples to underscore the benefits of good governance. I then present criteria for well‐governed financial institutions, specifically public and private pension funds, with implications for best practice as illustrated by four case studies of funds from Canada, Europe, and the United States. The final section considers the lessons of these case studies for the design of sovereign wealth funds and raises questions as to whether there are limits to reconciliation, given the acceleration of global financial integration.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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 it