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Record W4365801611 · doi:10.46692/9781447320883.024

Class: don’t mention the war!

2014· other· en· W4365801611 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typeother
Languageen
FieldSocial Sciences
TopicPolitical and Economic history of UK and US
Canadian institutionsnot available
Fundersnot available
KeywordsClass (philosophy)Computer scienceGenealogyHistoryArtificial intelligence

Abstract

fetched live from OpenAlex

‘Plutonomy’: for rich eyes only Combining plutocracy with economy, ‘plutonomy’ was a term coined in 2005–06 by Ajay Kapur of Citigroup, a major US financial group bailed out by the American people in 2008 after sustaining huge losses in the crash. It was introduced in a series of reports, the last of which was called The Plutonomy Symposium – Rising Tides Lifting Yachts . It was sent only to Citigroup’s wealthiest customers, but leaked to the press. It claims that the US, Canada, UK and Australia are the only plutonomies; much of continental Europe and Japan, which haven’t experienced such major upturns in wealth controlled by the rich, are ‘the Egalitarian Bunch’. According to the report, plutonomies have three key characteristics: 1. They are all created by ‘disruptive technology-driven productivity gains, creative financial innovation, capitalist friendly cooperative governments, immigrants … the rule of law and patenting inventions. Often these wealth waves involve great complexity exploited best by the rich and educated of the time.’ 2. There is no ‘average’ consumer in Plutonomies. There is only the rich ‘and everyone else’. The rich account for a disproportionate chunk of the economy, while the non-rich account for ‘surprisingly small bites of the national pie’. Kapur estimates that in 2005, the richest 20% may have been responsible for 60% of total spending. 3. Plutonomies are likely to grow in the future, fed by capitalist-friendly governments, more technology-driven productivity and globalisation. Democracy is potentially a threat: Perhaps the most immediate challenge to Plutonomy comes from the political process. Ultimately, the rise in income and wealth inequality to some extent is an economic disenfranchisement of the masses to the benefit of the few. However in democracies this is rarely tolerated forever. One of the key forces helping plutonomists over the last 20 years has been the rise in the profit share – the flip side of the fall in the wage share in GDP… However, labor has, relatively speaking, lost out. We see the biggest threat to plutonomy as coming from a rise in political demands to reduce income inequality, spread the wealth more evenly, and challenge forces such as globalization which have benefited profit and wealth growth. Nonetheless: Our own view is that the rich are likely to keep getting even richer, and enjoy an even greater share of the wealth pie over the coming years.

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.577
Threshold uncertainty score0.603

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0050.001
Scholarly communication0.0060.008
Open science0.0010.004
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.5770.452

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 head0.016
GPT teacher head0.263
Teacher spread0.247 · 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.

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
Published2014
Admission routes1
Has abstractyes

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