The Center On Federal Financial Institutions (COFFI) is a nonprofit, nonpartisan, nonideological policy institute focused on federal insurance and lending activities.
Bibliographic record
Abstract
44 million employees and retirees rely on the Pension Benefit Guaranty Corporation (PBGC) to help protect $1.5 trillion worth of promised pension payments. Unfortunately, PBGC faces an $11.2 billion deficit in its principal program, as of September 2003, a dramatic deterioration from the $7.7 billion surplus just two years earlier. We believe that coherent policy decisions on PBGC and pension issues need to start with answers to seven fundamental questions. • Are defined benefit pension plans better than defined contribution plans? (p. 2) • What are the purposes of PBGC? (p. 6) • How have pension plans changed over time? (p. 9) • How has PBGC’s universe of pension plans changed? (p. 11) • Are defined benefit plans on their way to extinction? (p. 15) • Is the PBGC deficit temporary or a symptom of structural problems? (p. 19) • Would tougher funding requirements cost jobs? (p. 23) Please see a companion piece, “PBGC: A Primer, ” issued simultaneously, for a non-technical explanation of PBGC and related pension and tax rules. We attempt to remain non-technical here as well but will presume knowledge of the subjects covered in the Primer. A neutral discussion of specific policy options is contained in another companion piece, “PBGC Policy Options: A Comprehensive Listing, ” to be issued in the second quarter of 2004. COFFI does not advocate any policy positions in these papers and we do not mean to endorse a position merely by stating an argument clearly. We will provide facts and quantification where these are relevant and available. Please see the “References ” section for more details on articles
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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".