MétaCan
Menu
Back to cohort
Record W2250116063

The Demographic Foundations of Rising Employment and Earnings Among Single Mothers in Canada and the United States, 1980 to 2000

2008· article· en· W2250116063 on OpenAlexaboutno aff
Feng Hou, Garnett Picot, Karen Myers, John Myles

Bibliographic record

VenueAnalytical Studies Branch Research Paper Series · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Labor, and Family Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsBaby boomEarningsDemographic economicsWelfareWelfare stateEconomicsBoomSingle mothersPopulationDemographic changeCohortDemographyLabour economicsPolitical sciencePsychologyMedicineSociology
DOInot available

Abstract

fetched live from OpenAlex

Despite comparatively modest welfare reforms in Canada relative to those of the United States, employment rates and earnings among single mothers have risen by virtually identical magnitudes in the two countries since 1980. We show that most of the gains in Canada and a substantial share of the change in the United States were the result of the dynamics of cohort replacement and population aging as the large and better educated baby boom generation replaced earlier cohorts and began entering their forties. In both countries, demographic effects were the main factor accounting for higher employment and earnings among older (40 and over) single mothers. Changes among younger single mothers, in contrast, were mainly the result of changes in labour market behaviour and other unmeasured variables. Overall, demographic changes dominated in Canada but not in the United States for two reasons: (a) Canadian single mothers are significantly older than their U.S. counterparts; and, (b) consistent with the welfare reform thesis, the magnitude of behavioural change among younger single mothers was much larger in the United States.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.027
Threshold uncertainty score0.197

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.061
GPT teacher head0.338
Teacher spread0.277 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueAnalytical Studies Branch Research Paper SeriesSame topicGender, Labor, and Family DynamicsFrench-language works237,207