Distributional Effects of Reducing the Social Security Benefit Formula
Bibliographic record
Abstract
A person’s Social Security benefit, or primary insurance amount (PIA), is 90 percent of the lowest portion of lifetime earnings, plus 32 percent of the middle portion of lifetime earnings, plus 15 percent of the highest portion of lifetime earnings. This policy brief analyzes the distributional effects of three options (the three-point, five-point and upper) discussed by the Social Security Advisory Board to reduce the PIA. The first option would reduce the PIA by 3 percentage points; the second would reduce it by 5 percentage points; and the third would reduce the 32 and 15 percentages of the PIA to 21 and 10 percent, respectively. The third option would exempt about one quarter of the lowest earning beneficiaries, while reducing benefits by a median average of 19 percent in 2070. None would eliminate Social Security’s long-term fiscal imbalance, although the third option would eliminate more (76 percent) of the deficit than the three-point (18 percent) and five-point (31 percent) options.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".