The Public Trust in Private Hands: Social Security and the Politics of Government Investment
Bibliographic record
Abstract
The funding crisis facing Social Security could be dramatically reduced if the $1.9 trillion accumulating in the Trust Fund were put into a diversified portfolio of stocks, bonds and other assets instead of the low yield U.S. Treasury certificates in which the Fund is currently invested. While the long term economic benefits of a diversified portfolio are largely undisputed, politicians cannot agree on whether the government or private individuals should make the investment decision. Republicans and Libertarians are philosophically opposed to government investment because of legitimate fears that politicians will interfere in corporate governance and steer money into investments that serve special interests. One reason Republicans advanced personal accounts as a solution to the funding crisis was because individual taxpayers, rather than the government, would make the investment decision. However, for a variety of reasons, the Republican personal accounts proposals are politically infeasible, and with time running out, a different strategy to leverage the private markets is needed. Another solution to the problems posed by government investment would be to create a federal government corporation (FGC) as an investment vehicle for the Social Security Administration (SSA). Historically, FGCs have played an important role in managing the nation's financial interests. Using an FGC as the investment arm for the SSA would distance the Fund from political influence so that professional investment advisors could make decisions based on wealth maximization rather than political influence. The solution has precedent in other countries. The Canadian government shifted its social insurance fund to a federal Crown corporation in 1997. The Crown corporation has not only remained politically neutral, it has also earned a higher rate of return than previous investments in government bonds. However, U.S. legal scholars question the legitimacy, accountability and transparency of American FGCs. Given the uncertain nature of the state action doctrine, it is not always clear whether an FGC is a state actor and therefore needs to comport with U.S. constitutional requirements as well as be subject to legislation governing federal agencies. This article explores the theoretical, constitutional and legal ramifications of creating a federal government corporation for the purpose of investing the $1.9 trillion Social Security Trust Fund in higher yield securities. The article concludes that not only can such an entity be consistent with democratic principles, it may be the best chance U.S. lawmakers have to address Social Security's funding crisis while mitigating anticipated tax increases and benefit cuts.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.029 |
| Scholarly communication | 0.015 | 0.012 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".