What happens to household portfolios after retirement
Bibliographic record
Abstract
The typical older household in the United States now arrives at retirement with an array of financial resources. These resources usually include home equity, vehicles, and bank accounts and may also include financial assets such as Individual Retirement Accounts (IRAs) and stocks or other property like small businesses and real estate. These assets are important for the financial security of older households. Households may use them to finance routine consumption in retirement or reserve them to cope with the financial consequences of a negative event like the death of a spouse. Households' ability to manage their assets in retirement is becoming more important over time, as the shift towards defined contribution pension plans means that households are more likely to receive their pension as a stock of assets at retirement rather than as a flow of monthly benefits. Older households hold a sizeable share of total U.S. household net worth, so the spend-down patterns of these households may affect asset markets, particularly as the large baby boom cohort enters retirement.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".