Bibliographic record
Abstract
Recent macroeconomic conditions have heightened anticipation that the Fed may act, perhaps sooner rather than later, to raise target Fed Funds off the historic lows of 0-25 basis points at which it has been held since December 2008. CME Group’s 30-Day Federal Funds futures contracts (Fed Funds futures) represent a direct reflection of collective marketplace insight regarding the future course of Fed monetary policy. In addition to their value as a predictive tool, Fed Funds futures also provide an efficacious means of hedging and gaining exposure to short-term interest rate risks. Macroeconomic Situation Improving economic conditions are now causing the Fed to consider “monetary policy normalization.” Minutes from the June 17-18th, 2014 FOMC meeting suggest that members recognize that “economic activity was rebounding in the second quarter following a surprising large decline in real GDP in the first quarter of the year. ” 1 Specifically, Q1-14 GDP checked in at-2.9%. But this disappointment is tempered by the fact that it was driven by inclement weather. On the other hand, “[l]abor conditions generally improved ” with the Jun-14 unemployment rate falling to 6.1%, as reported on Thursday July 3, 2014 and well below the Fed’s previously targeted
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.398 | 0.473 |
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".