Bibliographic record
Abstract
ven before the September 11 terrorist attacks, the prognosis for economic growth in the United States was not very encouraging.A little more than a year ago, a few brave souls prophesied the end of economic cycles.But despite end-of-term statements by the Clinton admi nistration about the health of what had been dubbed the U.S.'s "New Economy," by mid-2000 it was already showing signs of weakness and of the prospect of a recession before the end of 2001.The attack on two of the United States' most important symbols of its economic and military power was a death blow to the consumer confidence that had already begun to wane before the fatal events that devastated New York's World Trade Center, damaged the Pentagon and marked the end of the longest economic expansion that the country had ever seen.Now it will be practically impossible to distinguish between the long-awaited recessive trend and the negative impact that the attack inevitably had on the main macroeconomic indicators.Precisely because we are dealing with such a long expansion -it began in the second quarter of 1991-some optimists thought it could last indefinitely, while pessimists predicted a slump at the turn of every corner.But, in gener-
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.332 | 0.156 |
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".