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Record W7071703840

Three Papers on Retirement and Canada's Public Pension System

2022· dissertation· en· W7071703840 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

VenueMacSphere (McMaster University) · 2022
Typedissertation
Languageen
FieldComputer Science
TopicQR Code Applications and Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsReceiptEarningsPensionSample (material)Pension systemPublic policyLongitudinal dataLabour supplyPanel data
DOInot available

Abstract

fetched live from OpenAlex

In three chapters, I focus on how, and which, policy parameters of Canada’s public pension system affect seniors’ labour supply decisions. First, I study seniors’ labour supply responses to a series of reforms in 2012 and 2013 that incentivized many pensioners to extend their working lives; second, I assess how and whether receipt of public pension benefits affects seniors’ retirement timing differentially for those with different past earnings at ages 50-53; and, finally, I investigate older immigrants’ retirement and pension claiming decisions and how these decisions are impacted by permanent residency requirements for benefit eligibility. My analyses were carried out using income-tax and related panel data from the Longitudinal Administrative Databank (LAD), a 20% sample of taxpayers spanning the years 1982-2019 at the time of writing. In addition to detailed income-tax information, it contains information on receipt of non-taxable transfer income.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.985
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.014
GPT teacher head0.185
Teacher spread0.171 · 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