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Record W1593963845

The Role of Education in Enhancing Intergenerational Income Mobility

2007· article· en· W1593963845 on OpenAlex
Joann Wilkie

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

VenueEconomic round-up · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicIntergenerational and Educational Inequality Studies
Canadian institutionsnot available
Fundersnot available
KeywordsInequalityEconomic inequalitySocial mobilityEconomicsDemographic economicsIncome distributionLow incomeHousehold incomeDevelopment economicsLabour economicsGeographyPolitical science
DOInot available

Abstract

fetched live from OpenAlex

How income is transmitted from generation to generation is important to understanding the distributional impacts of policy. Compared with other OECD countries, labour income in Australia is relatively mobile across generations and Australia also has a moderate level of inequality, based on current household disposable income. OECD countries, with the exception of Canada, have either high inequality and low mobility or low inequality and high mobility. Education is an important factor influencing the extent to which income is transmitted from parent to child. The relatively high standard of minimum education outcomes in Australia and Canada, as reflected in the OECD’s Programme for International Student Assessment scores, are likely to play an important role in explaining Australia and Canada’s experience. Education outcomes alone, however, do not fully explain this combination of relatively high intergenerational income mobility and moderate income inequality.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.644
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.020
GPT teacher head0.346
Teacher spread0.326 · 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