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Record W1567636142

International Unit Labour Cost Position Has Slightly Deteriorated in 2007

2008· article· en· W1567636142 on OpenAlexaboutno aff
Alois Guger, Thomas Leoni

Bibliographic record

VenueWIFO Monatsberichte (monthly reports) · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicRegional Development and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsWageCzechUnit (ring theory)Labor costPosition (finance)Quarter (Canadian coin)Demographic economicsTotal costBusinessLabour economicsEconomicsGeographyEngineeringFinance
DOInot available

Abstract

fetched live from OpenAlex

In 2007, a working hour cost Austrian manufacturers 29.90 €, 7.8 percent more than the average of the other EU-15 countries. This amount consists of a wage share of 15.88 € plus 14.02 € in non-wage labour costs. At 88.3 percent, the incidental costs were slightly lower than in the previous year. In 2007, Austria ranked 11th in the international labour cost hierarchy. Labour was most expensive in Norway (one working hour in manufacturing was 33 percent more expensive than in Austria), followed by Belgium (+20 percent), Sweden (+17 percent), Denmark and Germany (+10 percent). Thanks to the exchange rate, Switzerland improved its position, although a working hour was still more expensive (by 8 percent) than in Austria. In France and the Netherlands the working hour cost more, in Finland the same as in Austria. In the UK and Ireland, manufacturers paid 10 percent less; in Italy the cost was one fifth lower than in Austria. The euro appreciation reduced the cost of a working hour in the USA; hence labour was in the USA by a quarter and in Japan by almost 40 percent cheaper than in Austria. In the new EU countries, labour cost a fraction of the Austrian rate: in Hungary, Estonia and the Czech Republic it was just about 20 percent, in Poland, Lithuania and Latvia 15 percent, and in Romania and Bulgaria less than 10 percent.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.029
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.005
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0010.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0290.022

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.

Opus teacher head0.054
GPT teacher head0.306
Teacher spread0.252 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2008
Admission routes1
Has abstractyes

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