Bibliographic record
Abstract
The study examines the current state of the US economy after the interest rate increases implemented by the Federal Reserve from January 2022 to July 2023 to reduce the rise in inflation. Although the Federal Reserve has successfully reduced inflation during this time period, the thesis of this paper is that future interest rate increases would be damaging to the economy and result in a recession. The five key economic indicators reviewed to assess the current state of the economy are (1) national debt, (2) real GDP growth rate, (3) inflation, (4) interest rate yield curve, and (5) unemployment. The conclusion of the paper is that the US Federal Reserve would damage several components of the economy if interest rate increases continue into the future, and it would increase the likelihood of a recession. The benefit of continuing with this monetary policy would be to decrease inflation from 3% to the publicly stated target of 2%. However, costs associated with this would be significantly higher since it would result in an increase in the US national debt and annual budget deficit because the servicing costs of the debt would increase dramatically. This would have a major impact on the US economy and eventually lead to an economic downturn.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 source (direct Gemma or distilled Codex), 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".