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Record W2906080883 · doi:10.1177/0081175019886613

The Intergenerational Elasticity of What? The Case for Redefining the Workhorse Measure of Economic Mobility

2020· article· en· W2906080883 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.

fundA Canadian funder is recorded on the work.
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

VenueSociological Methodology · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicIntergenerational and Educational Inequality Studies
Canadian institutionsnot available
FundersRussell Sage FoundationCanadian Institute for Advanced ResearchPew Charitable TrustsU.S. Department of Health and Human Services
KeywordsEarningsEconomicsEconometricsStock (firearms)Income elasticity of demandSocial mobilityElasticity (physics)SociologyGeographyFinance

Abstract

fetched live from OpenAlex

The intergenerational elasticity (IGE) has been assumed to refer to the expectation of children’s income when in fact it pertains to the geometric mean of children’s income. We show that mobility analyses based on the conventional IGE have been widely misinterpreted, are subject to selection bias, and cannot disentangle the different channels for transmitting economic status across generations. The solution to these problems—estimating the IGE of expected income or earnings—returns the field to what it has long meant to estimate. Under this approach, intergenerational persistence is found to be substantially higher, thus raising the possibility that the field’s stock results are misleading.

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)0.007
metaresearch head score (Gemma)0.015
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
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 score0.257
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
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 head0.514
GPT teacher head0.476
Teacher spread0.038 · 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