Self-Directed Brokerage Accounts:A First Look at Participant Investment Behavior
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
Although the industry has been tracking overall growth and assets in self-directed brokerage accounts (SDBAs) for some time, there is currently very little data on the investing behaviors and attitudes of SDBA participants. Schwab Corporate Services began tracking statistics on SDBA users in January 2001. The result is the SDBA Indicators, an ongoing compilation of key investment statistics and demographics on approximately 60,000 retirement plan participants investing in Schwab’s SDBA, the Schwab Personal Choice Retirement Account (PCRA). Data in this article reflect activity for the first quarter of 2002 and show that participants continued to move money into more conservative investments, as they did in 2001. The data also indicate that participants are using SDBAs as retirement plan sponsors intended, to help create diversified portfolios for long-term investment.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.011 | 0.008 |
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