Bibliographic record
Abstract
The information in this forecast is gathered by the Journal from sources it considers reliable. Neither the Journal nor the individual institutions providing the data guarantee accuracy; nor do any of them warrant in any way that use of the data appearing herein will enhance the business or investment performance of companies or individuals who use them.PARTICIPANTS I Beacon Economics = Los Angeles, California; Conf. Board = Conference Board, New York, New York; Fannie Mae = Fannie Mae, Washington, D.C.; Global Insight = Global Insight, Eddystone, Pennsylvania; GSU - EFC = Georgia State University, Economic Forecasting Center, Atlanta, Georgia; Moody's Economy = Moody's Economy.com, Westchester, Pennsylvania; Mortgage = Mortgage Bankers Association, Washington, D.C.; NAM = National Association of Manufacturers, Washington, D.C.; Northern Tr = Northern Trust Company, Chicago, Illinois; Perryman Gp = The Perryman Group, Waco, Texas; Royal Bank of Canada, Toronto, Ontario, Canada; SP UBS = UBS Bank, Salt Lake City, Utah; US Bank = U.S. Bank, Minneapolis, Minnesota; US Chamber = U.S. Chamber of Commerce, Washington, D.C.; Wells Fargo = Wells Fargo Bank, San Francisco, California.For most of us, it seems there are two salient issues: will this winter ever end and will the U. S. economy enter into a robust vibrant growth path? Regarding both, I offer a less than enthusiastic report. Undoubtedly, the cries regarding the return to another recession have diminished greatly; still there are many prognosticators worried about the fortunes of the U. S. economy this year. It is not a matter of a derailment as much as it is the over anticipation of 2014 being a breakout year. As always, Dr. Rajeev Dhawan of the Economic Forecasting Center at Georgia State University's J. Mack Robinson College of Business leads the way with an excellent and in-depth analysis of the situation as he sees it. Citing strong evidence from last year in unemployment, auto sales, housing, and a surging stock market, Dhawan counters with a less than a vibrant assessment regarding business investment spending prospects. At play here is the dismal outlookfor manufacturing related to the apparent weakness in China's economy, continual financing constraints realized by small businesses in general, and a less than rosy outlook for corporation's cash receipts. In addition, Dhawan looks disparagingly on job growth numbers related to the issue of quality. Despite the impressive job gains from last year, approximately one-third were in retail trade and hospitality sectors known for low-paying jobs. As such, income growth was not supported. John Silvia, Chief Economist for Wells Fargo, calls for trend-like growth around 2. …
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How this classification was reachedexpand
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 | 0.003 | 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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".