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Record W194097314 · doi:10.1177/003682370006400304

Inflation and Accumulation: The Case of Israel

2000· article· en· W194097314 on OpenAlexafffund
Jonathan Nitzan, Shimshon Bichler

Bibliographic record

VenueScience & Society · 2000
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Theory and Policy
Canadian institutionsYork University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsEconomicsHyperinflationDifferential (mechanical device)Profit (economics)Core (optical fiber)Inflation (cosmology)Keynesian economicsMonetary economicsNeoclassical economicsMonetary policy

Abstract

fetched live from OpenAlex

A new theoretical framework links inflation and accumulation, with the Israeli experience as a case study. The focal point is the process of differential accumulation by the largest core firms. The theory of differential accumulation suggests that the relative power of these firms can be augmented either through “breadth” (relative employment) or “depth” (relative profit per employee). In the Israeli case, inflation accelerated after the 1970s when the large core firm began shifting their emphasis from breadth to depth. The paper examines the political-economic conditions typical of each of these regimes, why these conditions changed in Israel, and how the distributive gains of the core firms pushed the country onto the brink of hyperinflation. It then articulates the inherent limits of a “depth” regime and shows how Israel reached those limits during the early 1980s, bringing the inflation spiral to an end.

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)0.002
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: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.004
Scholarly communication0.0040.002
Open science0.0000.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.044
GPT teacher head0.283
Teacher spread0.239 · 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

Citations7
Published2000
Admission routes2
Has abstractyes

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