Will Pre-Funding Provide Security for Social Security? A Review of the Literature
Bibliographic record
Abstract
Abstract: President Clinton has proposed creating larger social security funds and investing a portion of them in the private sector. Others have suggested more radical reforms such as moving social security from a defined-benefit scheme to a definedcontribution plan based on the Chilean model. These proposals are based on the goal of creating higher investment returns, which would make social security benefits easier to finance in the long run. The important public policy issues inherent in such proposals are numerous: questions of whether pre-funded social security plans are demographically immune; whether pre-funding social security can increase gross national savings and worker productivity; whether there are better ways to create a healthy economy; whether social security is best offered as a defined-benefit plan or a defined-contribution plan. This paper reviews each of these important public policy issues in the context of recent social security policy initiatives in Canada and the United States. After an extensive review of the literature, the paper concludes that greater prefunding of social security will not, of and by itself, create a more secure system. T
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.
How this classification was reachedexpand
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".