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Record W4244578260 · doi:10.1017/cbo9780511492419.003

Framework

2001· book-chapter· en· W4244578260 on OpenAlexaff

Bibliographic record

VenueCambridge University Press eBooks · 2001
Typebook-chapter
Languageen
FieldEconomics, Econometrics and Finance
TopicIndian Economic and Social Development
Canadian institutionsMount Saint Vincent UniversityDalhousie University
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

Introduction This book examines macroeconomic development of the industrial nations during the past 100 years. Among the more notable features of capitalism's progress over this period have been alternating episodes of superior and poor economic performance. The main task of the book is to develop and apply a framework that explains these episodes and the causal linkages between them. The episodes to be analysed include the Great Depression, the golden age that followed World War II, and the current episode of high unemployment that began in the 1970s. Underlying our explanation of these historical developments is an assumption about how developed capitalist economies function that contrasts sharply with the mainstream perception. Mainstream neoclassical thought sees a capitalist system as inherently self-regulating: given some exogenous disturbance, mechanisms operate to steer the economy back to its full employment growth path. In our view, capitalism is not self-regulating, nor is it doomed to self-destruct as some crude Marxian versions of capitalism's development claim. Instead, we see alternating episodes of superior and poor performance as a normal part of capitalist development, and trace them to structural changes. Those who would argue that capitalism is self-regulating (given the usual provisos) not only must believe that an invisible hand is rapidly and continuously clearing markets and providing the signals needed for ecient resource allocation; they must also believe that this same invisible hand is selecting the technologies and institutions from the evolving structural framework that guarantee markets work in this fashion.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.176
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0060.006
Open science0.0040.004
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.1760.055

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 head0.182
Teacher spread0.146 · 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 designTheoretical or conceptual
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
Published2001
Admission routes1
Has abstractyes

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