MétaCan
Menu
Back to cohort

Consumption Inequality in Canada, 1997 to 2009

2014· dataset· en· W6926345450 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.

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

VenueFederated Research Data Repository · 2014
Typedataset
Languageen
FieldMedicine
TopicMicrobial Natural Products and Biosynthesis
Canadian institutionsnot available
Fundersnot available
KeywordsGini coefficientInequalityConsumption (sociology)Imputation (statistics)Economic inequalityRentingIncome inequality metrics

Abstract

fetched live from OpenAlex

We assess the evolution of consumption inequality in Canada over the years 1997 to 2009. We correct the imputation of shelter consumption for homeowners to allow for unobserved differences in housing quality correlated with selection into rental tenure, and we account for measurement error in this imputation. Using the Surveys of Household Spending 1997-2009, we find that household-level consumption inequality measured by the Gini coefficient increased from 0.251 to 0.275 over 1997 to 2006, and then declined to 0.264 by 2009. The Gini coefficient for individual level inequality similarly followed a hump-shaped pattern: it increased from 0.199 in 1997 to 0.216 in 2006, and then fell to 0.207 in 2009. In contrast, the Gini coefficient for household level income inequality followed a similar hump-shaped pattern, but the post-2006 decline was large enough to entirely wipe out pre-2006 increase. We also explore a possible correction for tail non-response bias in inequality measurement, and find that the increase in measured consumption inequality is robust to this correction. This dataset was originally deposited in the Simon Fraser University institutional repository.

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)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.009
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.002
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 head0.129
GPT teacher head0.383
Teacher spread0.254 · 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