Fixing the Future: How Canada’s Usually Factious Governments Worked Together to Rescue the Canada Pension Plan (review)
Notice bibliographique
Résumé
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...
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,003 | 0,008 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».