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Record W2157500522 · doi:10.1353/cpp.0.0035

Fixing the Future: How Canada’s Usually Factious Governments Worked Together to Rescue the Canada Pension Plan (review)

2009· article· en· W2157500522 on OpenAlexvenueaboutno aff
Patricia O’Reilly

Bibliographic record

VenueCanadian Public Policy · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsPensionPoliticsRevenueStorytellingPolitical sciencePlan (archaeology)EarningsPublic administrationHistoryFinanceBusinessLawArt

Abstract

fetched live from OpenAlex

Reviewed by: Fixing the Future: How Canada’s Usually Factious Governments Worked Together to Rescue the Canada Pension Plan Patricia O’Reilly Fixing the Future: How Canada’s Usually Factious Governments Worked Together to Rescue the Canada Pension Plan by Bruce Little. Toronto: University of Toronto Press, 2008. Bruce Little tells an interesting policy story. Although the primary focus of the study is the Canada Pension Plan (CPP), it encompasses the wider Canadian retirement income system of general revenue and earnings-based public pensions and private pensions or retirement savings. This is essentially a financial study, and as an economics analyst and advisor, Little has presented a balanced financial and legal account. Fortunately for the reader, as a journalist he has also enlivened it with the social and political struggles embedded in the story. In other words, he has saved the rather dry subject matter with good storytelling. The book is replete with behind-the-scenes stories and telling quotes. It is an enjoyable read. Little’s subtitle signals his intent in presenting one of the few successful cases of extensive inter-governmental collaboration in Canada on a complex and politically difficult policy file. Beginning with the events of the 1960s, which led to the creation of the CPP (and sister Quebec Pension Plan), the author [End Page 516] lays out the federal-provincial intergovernmental dynamics that resulted in the overhaul of the CPP in the late 1990s. It is important to unravel the factors that lie in the path of intergovernmental collaboration on large policy files, particularly since there is an ongoing need for progress in many key policy sectors in the Canadian federation. However, it is a difficult task. Just telling a good policy story takes a great deal of time and effort. The factors involved are numerous, multifaceted, and prone to metamorphosis. Causality is elusive, and the uncovering of “near misses” in policy development reminds us that the story could easily have taken a turn and come out quite differently. Repeated calls for measures to avert the financial “crisis” of the CPP through the late 1970s to the late 1990s, when it became clear the money would run out, came to naught until an intergovernmental deal was struck in 1996. The reader comes away from this inter-governmental policy analysis with an enhanced understanding not only of the development of Canada’s pension policy but also of some policy mechanisms worth note, particularly collaborative intergovernmental forums such as a joint (federal-provincial) public consultation process and a joint investment board. There are also some interesting claims from the author and the interviewees with which to advance ongoing theoretical and methodological debates about policy drivers. In reading, I loosely noted 30 factors that were thought to have played an important role in bringing this policy to fruition. The author summarized these as good luck, good people, good package, and good public communications, but found the model not readily transferable for “resolving other federal-provincial disputes.” I might disagree with that. If you take Little’s “four broad reasons” for policy success at their face-value, he is right. It is impossible to replicate luck. It is notoriously difficult to produce “leaders” when needed, or even to retain good people on policy files for a reasonable duration. It is relatively unusual for pan-Canadian governments to agree on a balanced policy that accomplishes clear societal goals. And it is uncommon to achieve state-society consensus through communication on a policy decision that requires triage, between short-term costs and long-term benefits, especially. True, this success does not sound replicable. If, however, one reads this policy story using more of the analytical frameworks of the contemporary schools of both policy analysis and intergovernmental relations, one sees that there is something to be learned here about the influence of ideas, institutions, interests, and relationships on policy outcome, and the role the dynamic among them plays in intergovernmental policy capacity. While luck and timing are always helpful, good luck in Little’s analysis was mostly produced through the deliberate development of financial ideas about “fiscal probity” and legislative requirements for financial reporting. Good people, while sometimes ad hoc, were nurtured within...

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)0.002
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.533
Threshold uncertainty score0.929

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.008
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.017
GPT teacher head0.252
Teacher spread0.235 · 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 designNot applicable
Domainnot available
GenreReview

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
Published2009
Admission routes2
Has abstractyes

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