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Record W4416090811 · doi:10.1007/978-1-349-58802-2_905

Kuznets swings

2008· book-chapter· en· W4416090811 on OpenAlexaboutno aff
Solomos Solomou

Bibliographic record

VenueThe New Palgrave Dictionary of Economics · 2008
Typebook-chapter
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Growth and Productivity
Canadian institutionsnot available
Fundersnot available
KeywordsPeriod (music)Business cycleSmoothingFirst world warReal gross domestic product

Abstract

fetched live from OpenAlex

Kuznets swings refer to variations in economic growth with an average cyclical period of 20 years. The average period of the swings found varies depending on the specific smoothing and trend elimination techniques employed (Bird et al., 1965). Kuznets (1958), Abramovitz (1959) and Lewis and O’Leary (1955) found mean swings of 22, 14 and 19 years respectively. The existing historical evidence suggests that for the period before the First World War long swings were a pervasive aspect of national economic growth, being observed in a wide set of economies, including the United States, Argentina, Australia, Brazil, Britain, Canada, France and Germany (Solomou, 1987). Similar results have been reported for Japan (Ohkawa and Rosovsky, 1973; Ohkawa, 1979; Shinohara, 1962).

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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.027
Threshold uncertainty score0.090

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0020.004
Scholarly communication0.0050.005
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0270.009

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 head0.038
GPT teacher head0.190
Teacher spread0.152 · 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
GenreOther

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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