MétaCan
Menu
Back to cohort
Record W396426648

Austria Withstands Recession: Return to Positive Growth in Early 2013

2013· article· en· W396426648 on OpenAlexaboutno aff
Klaus Vondra

Bibliographic record

VenueMonetary Policy & the Economy · 2013
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGerman Economic Analysis & Policies
Canadian institutionsnot available
Fundersnot available
KeywordsEconomicsRecessionInflation (cosmology)Quarter (Canadian coin)UnemploymentReal gross domestic productSeasonal adjustmentAggregate demandMacroeconomicsMonetary policyGeography
DOInot available

Abstract

fetched live from OpenAlex

Austria’s economy expanded by 0.8% in 2012, whereas the euro area slipped into recession again. Growth in Austria was driven both by domestic demand and net exports. While the economic outlook for the euro area remains clouded for 2013 as well, Austrian economic growth is likely to accelerate in the first half of 2013, as forecast by the OeNB. However, the continued weakness of order books and uncertainty surrounding the formation of a government in Italy as well as the latest developments in Cyprus represent potential hurdles for the recovery. HICP inflation decreased in January and February after a period of rising and stagnant inflation rates in the second half of 2012 and is expected to ease further in the course of the year. The economic sluggishness has had repercussions on the labor market – unemployment is on the rise. Austria’s Economy Contracts Only Marginally in Q4 2012 Despite Global Weakness The first full set of national accounts data for the fourth quarter of 2012 indicates that Austrian GDP shrank by just 0.1% against the third quarter (in real terms, seasonally and working-day adjusted). Thus, output contracted perceptibly less in Austria than in Austria’s main European trading partners (Germany: –0.6%; Italy: –0.9%). Whole-year growth for 2012 amounted to +0.8% in Austria (in real terms, both seasonally and not seasonally adjusted). Growth was fueled not only by net exports, but also by domestic demand. The negative contribution to growth of inventory changes corroborates the general picture of uncertainty among economic agents. Klaus Vondra1

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)0.001
metaresearch head score (Gemma)0.003
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0040.002
Open science0.0000.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0070.005

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 head0.018
GPT teacher head0.211
Teacher spread0.194 · 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

Citations1
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueMonetary Policy & the EconomySame topicGerman Economic Analysis & PoliciesFrench-language works237,207