Bibliographic record
Abstract
Overview: Awaiting the first Fed rate hike Our world growth forecasts this month are unchanged at 2.5% for 2015 and 2.7% for 2016, but have dropped from 2.6% and 3% respectively in July. A key issue is how world growth will hold up as US rates start to rise. An initial Fed rate hike in December is in our baseline and has become increasingly likely over recent weeks given the US data flow. Arguably, global financial conditions have already started to tighten. US stocks have regained most of their August‐September losses but global stocks remain well below May's peak. Junk bond spreads have also widened since mid‐2015 and the latest credit standards surveys (see Research Briefing in this issue) had some worrying elements with a sharp worsening in emerging markets and less favourable readings in some advanced economies. Meanwhile, the slowdown in China and other emerging markets (EM) continues to weigh on global trade and industrial output. G7 industrial output is likely to have contracted for a second straight quarter in Q3 and manufacturing PMIs remain consistent with stagnant or declining output in most major EMs. The weakness in EM remains a major risk factor for the global economy as we move towards 2016, and could yet drag world growth down below this year's already‐moderate level. But so far, the difficult conditions in the industrial economy are not being mirrored in the services sector. In the advanced economies, services PMIs are mostly consistent with solid rates of expansion and have not shown a downward trend. This contrasts with the Eurozone crisis of 2011–12 when G7 services PMIs performed badly. The solid performance of service sectors has been accompanied by business confidence measures mostly holding up too, despite the serious wobble in stock markets in Q3. Overall, while our 2016 world growth forecasts are below consensus risks are skewed to the downside; in particular – despite developments to date – financial conditions could tighten more as Fed rate hikes begin.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.353 | 0.346 |
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".