MétaCan
Menu
Back to cohort
Record W2746569668 · doi:10.1093/ser/mwx027

Power, policy, and top income shares

2017· article· en· W2746569668 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSocio-Economic Review · 2017
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Theory and Policy
Canadian institutionsUniversity of Waterloo
FundersNational Science Foundation
KeywordsEconomicsIncome sharesFinancializationPoliticsIncome distributionLabour economicsInvestment (military)ProductivityMonetary economicsMarket economyMacroeconomicsInequality

Abstract

fetched live from OpenAlex

Abstract The rise of the super-rich has attracted much political and academic attention in recent years. However, there have been few attempts to explain the cross-national along with the temporal variation in the rise of top incomes. Drawing on the World Wealth and Income Database, we study the income share of the top 1% in current postindustrial democracies from 1960 to 2012. We find that extreme income concentration at the top is a predominantly political phenomenon, not the result of increasing marginal productivity of top managers in markets of increasing size. Top income shares are largely unrelated to economic growth, increased knowledge-intensive production, export competitiveness, financialization and wealth accumulation, though they are related to stock market capitalization. Instead, they are closely associated with political and policy changes such as union density and centralization, secular-right governments, top marginal tax rates and investment in public tertiary education.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.647
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.006

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 head0.305
Teacher spread0.267 · 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