MétaCan
Menu
Back to cohort
Record W3122709350

Unemployment in the Great Recession: A Comparison of Germany, Canada and the United States

2014· article· en· W3122709350 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueSSRN Electronic Journal · 2014
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicUnemployment and Economic Growth
Canadian institutionsUniversity of British ColumbiaUniversity of British Columbia Hospital
Fundersnot available
KeywordsUnemploymentRecessionGreat recessionEconomicsLabour economicsDemographic economicsPolitical scienceKeynesian economicsMacroeconomics
DOInot available

Abstract

fetched live from OpenAlex

This paper looks at the surprisingly different labor market performance of the United States, Canada, Germany, and several other OECD countries during and after the Great Recession of 2008-09. The unemployment rate followed a very different path in these countries. It barely increased in Germany, increased and remained at relatively high levels in the United States, and increased moderately in Canada. More recent data also shows that, unlike Germany and Canada, the U.S. unemployment rate remains largely above its pre-recession level. We find two main explanations for these differences. First, we show that the large employment swings in the construction sector linked to the boom and bust in U.S. housing markets is an important factor behind the different labor market performance of the three countries. Second, we find that cross-country differences are consistent with a conventional Okun relationship linking GDP growth to employment performance. Relative to pre-recession trends, there has been a much larger drop in GDP in the United States than Germany between 2008 and 2012, which helps account for a large fraction of the difference in employment performance between the two countries.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.320
Threshold uncertainty score0.793

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.016
GPT teacher head0.218
Teacher spread0.202 · 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