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Envy and Inequality*

2012· article· en· W1480596749 on OpenAlex
Francisco Alvarez‐Cuadrado, Ngo Van Long

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

VenueScandinavian Journal of Economics · 2012
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic theories and models
Canadian institutionsMcGill University
Fundersnot available
KeywordsBequestEconomicsOverlapping generations modelInequalityConsumption (sociology)Labour economicsDistribution (mathematics)Capital (architecture)Stock (firearms)Position (finance)Demographic economicsMathematics

Abstract

fetched live from OpenAlex

Abstract We present an overlapping generations economy, populated by heterogeneous agents who care about both consumption relative to others and the bequest they leave to their offspring. We show that saving and bequest rates vary across the income distribution, and we obtain several interesting results. First, envy reduces the steady‐state capital stock and increases the degree of inequality in consumption, capital ownership, and bequests. Second, if the bequest motive is sufficiently strong the equalizing effect of bequests disappears. Third, income inequality for a given cohort increases with age. Fourth, the distribution of inherited wealth becomes more unequal than that of wealth in general. Fifth, economic position becomes more persistent across generations.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.155
Threshold uncertainty score0.631

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 studies0.0000.000
Scholarly communication0.0000.001
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 head0.050
GPT teacher head0.220
Teacher spread0.170 · 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