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Record W2099874214

Evaluating Mobility Between Unmatched Quantiles: The Effects on Generational Mobility of Changes in Family Law in the United States.

2006· article· en· W2099874214 on OpenAlexaffabout
Gordon Anderson, Teng Wah Leo

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicIntergenerational and Educational Inequality Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEducational attainmentSocial mobilityQuantileProxy (statistics)Demographic economicsTransition (genetics)PopulationCensusEconometricsEconomicsDemographySociologyMathematicsEconomic growthStatisticsPolitical scienceChemistryLaw
DOInot available

Abstract

fetched live from OpenAlex

We thank participants at the CEPA seminars at University of Toronto, and at the Center for European This paper addresses the intergenerational mobility question by examining the role of family structure in the transmission of educational attainment using the one percent Integrated Public Use Microsample Series (IPUMS) of the decennial Census for the decades 1970 and 1990. We first introduce mobility indices and tests which examine the proximity of the transition matrix to that which would pertain in the perfectly mobile state. Unlike existing transition matrix based mobility indices, these indices and tests can be employed when the quantiles of the marginal states are unmatched, and when the transition matrix is between states that are defined multivariately. Using educational attainment as a proxy for permanent income for children and both educational attainment and income as proxies for parents, the tests indicate that mobility significantly increased for the population as a whole. Within the single parent group there was much less evidence for significant mobility change for children from widowed single parent families than for children from divorced and separated single parent families.

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.

How this classification was reachedexpand

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)0.005
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.779
Threshold uncertainty score0.879

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.153
GPT teacher head0.425
Teacher spread0.272 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2006
Admission routes2
Has abstractyes

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