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Record W1521991639

Recent Trends in Canadian Defined- Benefit Pension Sector Investment and Risk Management

2005· article· en· W1521991639 on OpenAlexvenueaboutno aff
Eric Tuer, Elizabeth Woodman

Bibliographic record

VenueBank of Canada review · 2005
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Literacy, Pension, Retirement Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsPensionValuation (finance)Equity (law)FinanceEconomicsInvestment (military)LiabilityBusinessPension planActuarial science
DOInot available

Abstract

fetched live from OpenAlex

Defined-benefit (DB) pension plans account for the majority of employer pension fund assets. In recent years, a number of DB plans have become underfunded, in sharp contrast to the 1990s, when many plans had large actuarial surpluses. The deterioration in the financial health of DB plans has underscored various longer-term structural issues that could make it increasingly difficult for plan sponsors to manage the financial risks of these plans. Tuer and Woodman examine how funding deficits, a greater focus on plan liabilities, a low yield environment, and changing investment beliefs are influencing investment decisions in the Canadian DB pension sector. They review the funding of DB plans, changing views on the equity-risk premium, and the shift towards liability-centred approaches to investment and how these developments are affecting pension sector investment. They also consider additional influences on the pension sector, including the limited supply of long-term bonds, the elimination of the foreign-property rule, and the movement towards fair-value accounting and a financial-economics approach to actuarial valuation, as well as their implications for financial markets.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.610
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.012
GPT teacher head0.211
Teacher spread0.199 · 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 designNot applicable
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

Citations6
Published2005
Admission routes2
Has abstractyes

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