MétaCan
Menu
Back to cohort
Record W2125591158 · doi:10.3138/cpp.2012-034

The Prince and the Pauper: Movement of Children up and down the Canadian Income Distribution

2014· article· en· W2125591158 on OpenAlex
Peter Burton, Shelley Phipps, Lihui Zhang

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.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCanadian Public Policy · 2014
Typearticle
Languageen
FieldDecision Sciences
Topicdemographic modeling and climate adaptation
Canadian institutionsUniversity of ReginaCanadian Institute for Advanced ResearchDalhousie University
Fundersnot available
KeywordsMicrodata (statistics)PovertyEquity (law)Demographic economicsIncome distributionDistribution (mathematics)EconomicsPanel Study of Income DynamicsDevelopment economicsEconomic growthPolitical scienceSociologyDemographyInequalityCensus

Abstract

fetched live from OpenAlex

This paper uses longitudinal microdata from the Statistics Canada National Longitudinal Survey of Children and Youth (NLSCY) to study the family income dynamics of Canadian children from the time they are 4 or 5 until they are 14 or 15. Dynamics of family income have been studied less often than dynamics of child poverty. Yet we argue that from the perspective of equity, it is important to know the extent to which some children are always affluent while other children are always poor. Also, since our social safety net is designed to shelter Canadians, including children, from both economic hardship and economic loss, it is also important, from the perspective of policy, to assess risk factors for persistent low income as well as correlates of major economic loss.

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)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
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 score0.723
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.026
GPT teacher head0.285
Teacher spread0.260 · 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