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Record W1990308623 · doi:10.1080/17441692.2015.1012528

The relevance of the public–private partnership paradigm to the prevention of diet-associated non-communicable diseases in wealthy countries

2015· article· en· W1990308623 on OpenAlexaffabout
Michael Stevenson

Bibliographic record

VenueGlobal Public Health · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Public Health Policies and Epidemiology
Canadian institutionsBalsillie School of International Affairs
FundersRockefeller FoundationInternational AIDS Vaccine InitiativeBill and Melinda Gates Foundation
KeywordsEconomic growthGeneral partnershipPovertyPublic healthPurchasing powerContext (archaeology)Government (linguistics)Development economicsPrivate sectorCorporate governanceBusinessPolitical scienceEconomicsMedicineGeographyFinance

Abstract

fetched live from OpenAlex

The public-private partnership (PPP) paradigm emerged as a form of global health governance in the mid-1990s to overcome state and market failures constraining access to essential medicines among populations with limited purchasing power in low- and middle-income countries. PPPs are now ubiquitous across the development spectrum. Yet while the narrative that the private sector must be engaged if complex health challenges are to be overcome is now dominant in development discourse, it does not yet appear to be shaping government approaches to addressing health inequalities within high-income welfare states such as Canada. This is significant as both the actions and inactions of firms factor heavily into why low-income Canadians face a disproportionate risk of developing diet-associated chronic diseases, such as type II diabetes. In the same ways PPPs have been an effective policy tool for strengthening public health in poor countries, this paper illuminates how the PPP model may have utility for mitigating poverty-associated food insecurity giving rise to diet-associated non-communicable diseases within the context of wealthy states.

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)0.009
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.803
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0020.001
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 head0.075
GPT teacher head0.344
Teacher spread0.269 · 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

Citations10
Published2015
Admission routes2
Has abstractyes

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