Bibliographic record
Abstract
Overview: Monetary stances shifting but markets still calm US growth for Q1 was revised down very sharply, so that despite an expected bounce in Q2, we have cut our 2014 GDP forecast for the US further this month to 1.5% from 2.1% last time. Despite this, we have brought forward our forecast of the first Fed rate hike by one quarter to Q2 2015. In part this reflects broad labour market improvements, which continued in June with buoyant payrolls growth and unemployment dropping to close to 6% – compared to nearly 8% at the start of last year. The start of monetary tightening is also getting closer in the UK, where with GDP growth at 3% we now see the first increase in rates as early as Q4 of this year. Meanwhile, policy is getting looser in the Eurozone. The ECB is now talking about an ‘extended period’ of very low short‐term rates and we expect no rate hike until Q2 2017. The ECB's June policies have so far failed to produce any significant euro weakness, however. As a result, with survey data now suggesting the Eurozone recovery may be softening, the danger of a lengthy period of very low inflation and weak output growth remains high. In our view Japan also needs to loosen policy further. The existing QE programme is not delivering a sufficiently strong monetary impulse to offset fiscal tightening, risking a slump in growth over the next few quarters unless the BoJ moves fast. These divergent moves in monetary stances among the advanced economies are as yet not unsettling financial markets. Global growth remains sub‐par, now forecast at 2.6% for this year and 3.1% next, but the outlook is not yet weak enough to disturb the narrow spread and low volatility environment. Probably the main near‐term risk is renewed problems in the emergers. Forecasts are again mostly stable this month (excepting another cut in Brazil) and financial conditions fairly benign. But structural challenges in the BRICs, geopolitics and serious imbalances in some countries retain the potential to generate a shift in global financial conditions.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.408 | 0.427 |
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".