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Guaranteed Income Supplement (GIS) Status Amongst the Retired Population: An Analysis of the Incidence

2013· article· fr· W1983702932 on OpenAlexaffvenueabout
Ross Finnie, David Gray, Yan Zhang

Bibliographic record

VenueCanadian Public Policy · 2013
Typearticle
Languagefr
FieldSocial Sciences
TopicRetirement, Disability, and Employment
Canadian institutionsStatistics CanadaUniversity of Ottawa
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Dans cet article, nous évaluons le taux d’incidence, chez les Canadiens de 65 ans et plus, du fait d’être bénéficiaire de prestations de la Sécurité de la vieillesse. La variable dépendante que nous modélisons est le taux d’incidence du fait d’être bénéficiaire de prestations de Supplément de revenu garanti (SRG). Nous estimons des équations multivariées afin de déterminer les effets de l’âge, de la cohorte, du statut matrimonial, de la province de résidence, du fait d’habiter en milieu urbain ou rural, et du fait d’être né au Canada ou non. Nous incluons également dans notre estimation les variables retardées qui portent sur le revenu et l’épargne au cours de la période précédant la retraite. Nos résultats montrent que le taux d’incidence estimé en fonction de la plupart de ces variables exogènes est assez élevé. Nous notons tout particulièrement que, toutes choses étant égales par ailleurs, les Canadiens vivant avec un conjoint ou une conjointe sont beaucoup moins susceptibles de recevoir des prestations SRG.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.190
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.005
Science and technology studies0.0010.002
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.104
GPT teacher head0.376
Teacher spread0.273 · 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.

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

Citations10
Published2013
Admission routes3
Has abstractyes

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Same venueCanadian Public PolicySame topicRetirement, Disability, and EmploymentFrench-language works237,207