Bibliographic record
Abstract
The dampening impact of the international cyclical slowdown on Austrian exports and business investment is being exacerbated by a decline in construction activity: in April and May, the sector's gross output fell by an inflation-adjusted 8 percent below the year-earlier level. Domestic manufacturing output held up well against the international cyclical slowdown until spring, but has since shown clear signs of weakening. In the second quarter, the production index was no higher than a year ago, having gained 6 percent during the first three months of the year. Exports and investment have also lost much of their previous momentum. Still more critical than in manufacturing, however, is the situation in the construction sector. In April and May, nominal output fell by 6½ percent year-on-year, or by 8 percent at constant prices. Particularly severe was the slump in residential construction (–14½ percent); gross output also fell in civil engineering. The sharp downturn is confirmed by the labour market statistics: 14, 000 construction jobs were lost from the previous year in the second quarter, and unemployment edged up by 3, 000. Leading business climate indicators do not yet support hopes for an imminent turnaround. Industrial confidence has weakened further in the third quarter. Results from the regular WIFO business survey have pointed down for the fifth time in a row. Sentiment in the construction sector has taken a steep fall. Exports remained surprisingly strong from January to April, gaining 10 percent year-on-year. In May, however, they failed to reach the year-earlier level, a reversal that is broadly in line with the slowdown abroad and firms' more pessimistic judgement on export orders. Tourism is currently providing major support to overall activity. The summer season has taken an encouraging start, with gross revenues from May to July rising by 5.2 percent from last year. Higher net earnings from cross-border tourism services are also largely responsible for an improvement in the current account. Consumer demand was still lively in the first quarter, but abated in the following period. Volume retail sales decelerated, while new car registrations declined. Wholesale trade was moreover affected by the slackening of exports and investment. Labour statistics for the trade sector, on the other hand, showing a net increase in the number of jobs and unemployment falling until mid-year, suggest a somewhat better situation. Labour market conditions overall are reflecting the cyclical slowdown. The year-on-year gains in employment (excluding people on parental leave and in military service) have narrowed to 0.4 percent by August, the number of unemployed is up by 15, 300. The seasonally adjusted rate of unemployment (as calculated by the labour market service) has moved up to 6 percent.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".