Charging into Adulthood: Credit Cards and Young Consumers
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
The New York Fed’s Center for Microeconomic Data today released the Quarterly Report on Household Debt and Credit for the fourth quarter of 2019. Total household debt balances grew by $193 billion in the fourth quarter, marking a $601 billion increase in household debt balances in 2019, the largest annual gain since 2007. The main driver was a $433 billion annual upswing in mortgage balances, also the largest since 2007. Auto loan and credit card balances both increased by a brisk $57 billion last year, while student loan balances climbed by a more muted $51 billion, well below the $114 billion increase recorded in 2013—the fastest pace of growth for the series. The source for the Quarterly Report is the New York Fed’s Consumer Credit Panel—a panel data set that now spans twenty-one years, 1999-2019. The unique panel design allows us to identify new entrants to the credit market: as young people age into having credit reports and using credit products, they are “born” into the panel, enabling us to observe the credit behavior of young borrowers.
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 | 0.000 | 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 | 0.000 | 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) | 0.000 | 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 it