U.S. Minority Depository Institutions at the Dawn of the Twenty-First Century
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
In the current era of intensified global migration and economic change, the simultaneous movement of people, money, services, and information alter the socioeconomic demographic makeup as well as the financial dynamics of countries. Building on our previous work on ethnic banking, this article examines the size, nature, and capacity of the new minority depository institutions (MDIs) in the United States. It identifies the reasons for the establishment of these new MDIs and their distribution in relation to immigration dynamics, and observes the role of social capital in their operation. It finds that contemporary financial dynamics pertaining to immigrants and minorities is rooted and localized in different ways and with different groups. Some MDIs are more globally connected or less locally embedded than others. Their utilization of social capital or ethnic assets also varies. In asserting that global financial situations and global money flows have significantly affected the emergence of MDIs, we suggest some policy interventions to facilitate the healthy growth of MDIs.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it