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 inequality of earnings and of family incomes in the United States has increased since the late 1970s. The large rise in earnings inequality between the 1970s and the 1990s could reflect either a rise in disparity of permanent incomes, a rise in earnings instability, or some portion of both. In this paper, we provide longitudinal measures that separate changes in income inequality into changes that permanently change income to new levels and those that only reflect transitory change. We refer to the latter as changes in “income instability” and discuss how the instability of individual earnings and family income in the United States has evolved— as whole as well as for different types of individuals and families—over the last quarter century. We consider alternative definitions of instability that have been proposed, and establish that all studies find that instability is considerably higher today than in the mid-1970s. This increase in instability is not a recent phenomenon. Earnings instability rose sharply in the late 1970s and early 1980s, then stabilized at these high levels through the recent period, although it may be increasing once again. We also discuss the factors that may be driving this increase in instability.
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 | 0.002 | 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 | 0.000 | 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