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Record W2965098085 · doi:10.1425/93581

Income inequality and stagnation in Italy over the last quarter of a century

2019· article· en· W2965098085 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueStato e mercato · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicItaly: Economic History and Contemporary Issues
Canadian institutionsnot available
Fundersnot available
KeywordsRecessionEconomicsInequalityBusiness cycleQuarter (Canadian coin)Economic inequalityPovertyCurrencyDemographic economicsPopulationEconomic stagnationDevelopment economicsGeographyMonetary economicsKeynesian economicsEconomic growthPolitical scienceDemography

Abstract

fetched live from OpenAlex

The paper analyses the evolution of inequality in Italy from 1989 to 2014, focusing on three business-cycle phases: the 1992 currency crisis, the moderate growth from 1993 to 2007, and the double-dip recession from 2008 to 2013. Data from the national accounts and the Bank of Italy's Survey on Household Income and Wealth are used. Income inequality rose sharply during the recession of the early 1990s but much less during the recent double-dip recession, though the share of people at risk of poverty rose similarly during the two crises. This follows from the fact that the reduction in income hit the whole population during the double-dip recession. This apparent stability hides the widening gap between socio-demographic groups, in particular between the young and the elderly, and between native and foreign-born households.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.122
Threshold uncertainty score0.489

Codex and Gemma teacher scores by category

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

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 head0.015
GPT teacher head0.213
Teacher spread0.198 · 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