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Record W2253002063 · doi:10.55016/ojs/sppp.v6i1.42432

The Fiscal, Social and Economic Dividends of Feeling Better and Living Longer

2013· article· en· W2253002063 on OpenAlexaffabout
Ludovic Brunel, Daniel J. Dutton

Bibliographic record

VenueThe School of Public Policy Publications · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsFeelingDividendEconomicsEconomic policyPublic economicsBusinessPsychologySocial psychologyFinance

Abstract

fetched live from OpenAlex

While Canada has socialized most of the costs of treating illness, Canada has maintained a reliance on individuals interacting through private markets to invest in upstream health promotion and disease prevention. The failure of the market to provide the efficient level of upstream investment in health is leading to large and avoidable increases in the need for downstream medical treatment. The way to reduce the future deadweight loss of illness and disease is for provincial governments to address the upstream market failures through an expansion of the scope of public payment for health care to include upstream services for health promotion and disease prevention. Perhaps somewhat counterintuitively, spending public health-care dollars across a broader range of health and wellness services can result in spending less in total, because of the efficiency gains that will come from better health in the population. That is certainly what the evidence from a unique Albertan pilot project leads us to conclude. The Pure North S’Energy Foundation is a philanthropic initiative that pays for and provides preventative health-care services for Albertans drawn from groups that are vulnerable to poor health. This includes homeless people, people suffering from addiction, people with low incomes, people in isolated areas and susceptible seniors. The health improvements observed in those participating in the Pure North program have been significant. Effective health-promotion and disease-prevention services obviously benefit patients. But there are also substantial benefits to society as well. The annual health-care bill for a Canadian in poor health is estimated to be more than $10,000 higher than for someone in good health, meaning that keeping people in good health can be an important means for controlling public health-care budgets, and can free up scarce acutecare hospital resources. If the Pure North program were scaled-up province-wide to cover the nearly quartermillion Albertans in poor health, the resulting health improvement seen in Pure North participants could translate into a nearly 25-per-cent reduction in hospital days used by Alberta patients every year and a net savings of $500 million on hospital and physician costs. That does not even include the economic benefits of keeping workers in better health and productive, while spending fewer days ill or hospitalized. To date, Canada’s approach to health care has largely left it to patients to choose whether to seek healthpromotion and disease-prevention services on their own, suggesting an implicit deference to an individual’s rights and responsibilities. But for many low-income, isolated, addicted or aboriginal Canadians, there often is no choice: These services, when delivered privately, are often too expensive or may be otherwise inaccessible. The initial spirit behind Canadian medicare was to correct a health-market failure, so that no patient would face barriers to accessing necessary treatments. That same philosophy also recommends extending universal coverage for health-promotion and disease-prevention to vulnerable Canadians who today face similar barriers to access. If the Alberta government wants to show both foresight and fairness, the benefits from this kind of program, economically and societally, are simply too attractive to disregard.

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)0.003
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.988
Threshold uncertainty score0.472

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0060.010
Scholarly communication0.0060.005
Open science0.0010.006
Research integrity0.0010.005
Insufficient payload (model declined to judge)0.0170.001

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 head0.035
GPT teacher head0.307
Teacher spread0.273 · 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 designTheoretical or conceptual
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

Citations0
Published2013
Admission routes2
Has abstractyes

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