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
In his Nobel Prize acceptance speech given in 1985, Franco Modigliani drew attention to the “annuitization puzzle”: that annuity contracts, other than pensions through group insurance, are extremely rare. Rational choice theory predicts that households will find annuities attractive at the onset of retirement because they address the risk of outliving one's income, but in fact, relatively few of those facing retirement choose to annuitize a substantial portion of their wealth. There is now a substantial literature on the behavioral economics of retirement saving, which has stressed that both behavioral and institutional factors play an important role in determining a household's saving accumulations. Self-control problems, inertia, and a lack of financial sophistication inhibit some households from providing an adequate retirement nest egg. However, interventions such as automatic enrollment and automatic escalation of saving over time as wages rise (the “save more tomorrow” plan) have shown success in overcoming these obstacles. We will show that the same behavioral and institutional factors that help explain savings behavior are also important in understanding 1) how families handle the process of decumulation once retirement commences and 2) why there seems to be so little demand to annuitize wealth at retirement.
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.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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 it