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Record W1606477231

Summary Of: The Instability of Family Earnings and Family Income in Canada, 1986 to 1991 and 1996 to 2001

2005· preprint· en· W1606477231 on OpenAlexaboutno aff
René Morissette, Yuri Ostrovsky

Bibliographic record

VenueRePEc: Research Papers in Economics · 2005
Typepreprint
Languageen
FieldSocial Sciences
TopicGender, Labor, and Family Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsEarningsEconomicsContext (archaeology)Family incomeDemographic economicsLabour economicsInstabilityVolatility (finance)Economic stabilityFinancial economicsGeographyFinanceEconomic growthMacroeconomics
DOInot available

Abstract

fetched live from OpenAlex

This article summarizes findings from the research paper entitled: The Instability of Family Earnings and Family Income in Canada, 1986 to 1991 and 1996 to 2001. Despite its implications for family well-being, little attention has been paid to the analysis of earnings instability in the context of the family versus the earnings profiles of individuals. While a focus on individuals is important, the extent to which families can generate stable income flows from the labour market is a key concern for policymakers. Therefore, using data from Statistics Canada's Longitudinal Administrative Databank (LAD), this study documents how family earnings instability has evolved between two six-year periods: 1986-1991 and 1996-2001. We also examine how husbands' earnings instability compares to couples' earnings instability, and we compute measures of instability based on family earnings, family market income, and family income before and after tax. This allows us to examine the extent to which wives' earnings reduce the volatility of husbands' employment income; the extent to which the tax and transfer system plays a stabilization role; and the extent to which wives' earnings, taxes, and transfers reduce the differences in instability between couples in the bottom of the earnings distribution and those in the top.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.076
Threshold uncertainty score0.955

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0000.001
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 head0.030
GPT teacher head0.304
Teacher spread0.274 · 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
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueRePEc: Research Papers in EconomicsSame topicGender, Labor, and Family DynamicsFrench-language works237,207