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Record W3126127853

Critical Condition: A Historian's Prognosis on Canada's Aging Healthcare System

2010· preprint· en· W3126127853 on OpenAlexaboutno aff
Michael Bliss

Bibliographic record

VenueTSpace (University of Toronto) · 2010
Typepreprint
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsBLISSDeferenceHealth carePolitical sciencePoliticsPublic administrationPolitical economySociologyLaw
DOInot available

Abstract

fetched live from OpenAlex

Foreword
\nWhen a set of public policies fundamental to our wellbeing is so politically sensitive and shot
\nthrough with conflicting real and perceived conflicts of interest as to produce paralysis, a smart
\nand wise historian can often provide the long-term, evolutionary perspective required to find the
\nmore promising ways forward. Canadian healthcare is fundamental to our wellbeing and so
\npolitically charged that despite its widely perceived shortcomings, attempts at fundamental reform
\nappear the electoral equivalent of touching the proverbial third rail on a subway track. Professor
\nMichael Bliss is one of Canada’s most able and eminent historians. The C.D. Howe Institute’s 2010
\nBenefactors Lecture is his attempt to take stock of publicly funded healthcare in Canada in the light
\nof how it came to be, and give his assessment of the right directions forward to ensure that it serves
\nCanadians well in the decades ahead.
\nA good historian draws from many disciplines, and Professor Bliss’s account draws on
\ninsights from medicine, political science, economics, and much else. His account of the
\ndevelopment of what Canadians nowadays call “medicare” from provincial coverage of doctor and
\nhospital services in the 1960s through the federal Canada Health Act in the 1980s and the
\nalternating dips and boosts in spending in the 1990s and 2000s is clear and compelling. Without
\nundue deference to any particular perspective, he argues convincingly that an economically
\nadvanced democratic society will devote a growing share of its resources to healthcare, and that
\nCanadians’ support for access to it is a fact of life that even medicare’s more vociferous critics must
\naccommodate in their reform proposals.
\nWhen it comes to his own advice for reform, Professor Bliss puts forward some
\npropositions that will – like all changes to healthcare – inevitably be controversial. He draws on
\nexperiences with other major programs in the Canadian welfare state, family and old-age benefits
\nin particular, to argue that reducing public commitments to the healthcare of Canadians who are
\nable to pay their own way is both fiscally necessary and politically acceptable. Hence, he
\nencourages the evolution of our health insurance system from providing universality of benefits
\nonto a needs basis, preserving the core value of equal access. Economists and others concerned
\nwith the way income- and asset-related withdrawal of benefits from the better off have produced
\nwelfare walls and high effective marginal tax rates on modest-income people will have reservations
\nabout this proposal. If he is right that it is the way out of the chronic fiscal squeeze that otherwise
\nlooms, however, the challenge is to craft the most adept way to do it.
\nIn an age of reduced deference to experts of all kinds, Professor Bliss’s second
\nrecommendation – that Canadians accept that medical researchers and practitioners should play
\na more prominent role in determining what is medically necessary – will also raise objections. It
\nmay presuppose a level of confidence in professional expertise, and improved standards for
\nresearch and practice that would justify that confidence, that medicine, like all fields, has yet to
\nachieve. Yet the importance of specialized knowledge in determining what is likeliest to work is so
\ncritical in medicine that the problems of letting third parties, including health ministries, overrule
\nresearchers and practitioners in the field oblige us to take this advice seriously.
\nProfessor Bliss’s third observation is less about how to move forward than it is about not
\nstaying stuck where we are. Whatever the devotion of some Canadians and a handful of advocates
\nabroad to a single-payer government monopoly model may be, he points out that no other
\ndeveloped country has imitated it, and none is about to. Canada’s current approach is a product
\nof specific Canadian circumstances, not least of which is its emblematic status as a differentiator
\nof Canada from the United States – hardly a sound basis for determining how to provide and pay
\nfor the vast array of medical services that determine how healthy or sick we are, and even whether
\nwe live or die. His appeal to use more market mechanisms to harness the incentives of producers
\nand patients in the service of better outcomes, rather than lamenting or denouncing them, is a
\ngeneral exhortation. In practice, it will require balancing against his other suggestions to abandon
\nuniversality and defer more to medical expertise. Yet there can be no doubt that any reform that
\ndoes not harness these incentives effectively cannot hope to succeed.
\nThe C.D. Howe Institute’s Benefactors Lecture is intended to encourage better understanding
\nof major Canadian public policy challenges, and stimulate debate about how best to meet them.
\nMany people besides Professor Bliss deserve credit for producing the 2010 version of the Lecture:
\nI thank Pfizer for their financial support, the reviewers of earlier drafts for their comments, Barry
\nNorris and James Fleming for their editing, and Bryant Sinanan for his page layout. As with all the
\nInstitute publications, the opinions expressed here are those of the author, and do not necessarily
\nrepresent the views of the Institute’s members or Board of Directors. I commend Professor Bliss
\nfor having ably responded to the challenge of addressing the condition of Canadian healthcare,
\nhowever, and hope all readers will take from it his valuable insights about how we got where we
\nare, and what can help us do better.
\n(William B.P. Robson
\nPresident and Chief Executive Officer
\nC.D. Howe Institute)

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)0.000
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: none
Teacher disagreement score0.932
Threshold uncertainty score0.998

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.020
GPT teacher head0.284
Teacher spread0.264 · 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
Published2010
Admission routes1
Has abstractyes

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