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Record W3123279278

The Great Pension Debate: Finding Common Ground

2019· article· en· W3123279278 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

VenueC.D. Howe Institute Commentary · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsPensionPlan (archaeology)PersuasionPoint (geometry)Pension planCommon groundActuarial scienceBusinessFinancePsychologyHistorySocial psychology
DOInot available

Abstract

fetched live from OpenAlex

In the never-ending debate about finding an optimal pension model, many proponents start the discussion at extreme ends of the pension model paradigm. At one extreme is a traditional, fully guaranteed defined-benefit (DB) pension plan. In this plan, all of the risks are born by the plan sponsor given that plans are fully funded. While such plans are growing rare today that is the starting point for many in this debate. At the other extreme is a traditional defined-contribution (DC) plan. In this plan, all of the risks are borne by the worker participant. This, again, is a starting point for many in the pension model debate. Many classic DB and classic DC pension plans have not achieved their goals. This paper argues they should be replaced by pension plans that facilitate sharing of risks among all willing stakeholders, whether the plan is characterized as DB or DC. This paper proposes, as a starting point for all pension-plan model discussions, a “Common Ground.” If one is of a pro-DB persuasion, then the Common Ground model would be a Pooled Target Benefit DB pension plan. If one is of the pro-DC persuasion, then the starting point will be a large Collective DC plan. These plans have a lot in common and, since they can provide equivalent benefits for the same contributions, they should be viewed as being actuarially equivalent. Thus, by finding the common ground in the Great Pension Debate, we have also identified models for pensions that can provide all Canadian workers with significant retirement income security. With that accomplished, the question becomes whether one wants a bit more of a DB flavour and why or whether one wants a bit more of a DC flavour and why. This should make arriving at a consensus plan model much easier for all. We conclude that policies encouraging larger collective, pooled pension plans governed by independent management boards are very much needed to better serve Canadians. Such solutions are common in the public sector but need to be encouraged in the private sector.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.138
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 studies0.0020.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.033
GPT teacher head0.301
Teacher spread0.268 · 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