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Record W2114461056 · doi:10.1093/jae/ejm019

An Economic History of South Africa: Conquest, Discrimination and Development

2008· article· en· W2114461056 on OpenAlexaboutno aff
J. Bluemenfeld

Bibliographic record

VenueJournal of African Economies · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicSouth African History and Culture
Canadian institutionsnot available
Fundersnot available
KeywordsDemiseContext (archaeology)Per capitaPer capita incomeEconomicsDevelopment economicsEconomyGeographyEconomic historyPolitical scienceSociologyDemographyLaw

Abstract

fetched live from OpenAlex

This book represents the first major foray by the late Charles Feinstein—the renowned UK economic historian—into academic analysis of his country of birth. It is also the first comprehensive economic history of South Africa to incorporate not only the two decades after 1948 during which the policies and institutions of apartheid were articulated and imposed, but also the subsequent two decades during which these structures were weakened and undermined. Writing 10 years after the formal demise of apartheid, Feinstein has been able to set the economic characteristics of those turbulent final years in the context of the longer-term record of South Africa's growth and development. Feinstein begins, however, by considering that record in its comparative international perspective, and finds that the ‘most striking feature of this comparison over eight decades is the remarkable long-run deterioration in South Africa's relative performance, from one of the best economies … to one of the worst’ (p. 5). Drawing on a sample of thirty ‘comparable market economies’, he charts South Africa's growth performance in three periods—1913–50, 1950–73 and 1973–94—against the average growth in GDP per capita for several developed and developing regions or groupings (including the other former British Dominions of Canada, Australia and New Zealand).

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: none
Teacher disagreement score0.024
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.006
Science and technology studies0.0060.005
Scholarly communication0.0040.003
Open science0.0000.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.038
GPT teacher head0.239
Teacher spread0.201 · 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

Citations5
Published2008
Admission routes1
Has abstractyes

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