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Record W2136967731 · doi:10.1257/000282803322156972

Animal Spirits Through Creative Destruction

2003· article· en· W2136967731 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.

Bibliographic record

VenueAmerican Economic Review · 2003
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic theories and models
Canadian institutionsQueen's UniversityUniversity of British Columbia
Fundersnot available
KeywordsAnimal spiritsEconomicsBoomCreative destructionBusiness cycleVolatility (finance)Profit (economics)WelfareProductivityMicroeconomicsMacroeconomicsMarket economyEconometrics

Abstract

fetched live from OpenAlex

We show how a Schumpeterian process of creative destruction can induce rational, herd behavior by entrepreneurs across diverse sectors as if fueled by “animal spirits.” Consequently, a multisector economy, in which productivity improvements are made by independent, profit-seeking entrepreneurs, exhibits regular booms, slowdowns, and downturns as part of the long-run growth process. Our cyclical equilibrium has higher average growth, but lower welfare than the corresponding acyclical one. We show how a negative relationship can emerge between volatility and growth across cycling economies, and assess the extent to which our model matches several features of actual business cycles.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.897
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.004

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 head0.036
GPT teacher head0.265
Teacher spread0.229 · 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