MétaCan
Menu
Back to cohort
Record W2064170359 · doi:10.1080/17441690701438128

Time for an ecosystem approach to public health? Lessons from two infectious disease outbreaks in Canada

2009· article· en· W2064170359 on OpenAlex
Neil Arya, John M. Howard, S Isaacs, Mary Louise McAllister, Stephen D. Murphy, David J. Rapport, David Waltner‐Toews

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueGlobal Public Health · 2009
Typearticle
Languageen
FieldMedicine
TopicZoonotic diseases and public health
Canadian institutionsUniversity of GuelphWestern UniversityMcMaster UniversityUniversity of Waterloo
FundersHealth Canada
KeywordsPublic healthOutbreakCorporate governanceInfectious disease (medical specialty)DiseaseEcosystem healthPolitical sciencePublic relationsMedicineEnvironmental resource managementEcosystemEcosystem servicesBusinessEcologyVirologyEconomicsBiologyNursing

Abstract

fetched live from OpenAlex

Ecosystem approaches recognize the complexity of many contemporary public health challenges and offer an alternative for dealing with problems that have proven intractable and unresponsive to conventional public health strategies. Infectious disease outbreaks are among the most dramatic aspects of systems failure, and the Canadian cases of SARS (Severe Acute Respiratory Syndrome) in Toronto, and the E. coli outbreak in Walkerton, serve as useful illustrative examples. This paper examines some of the limitations of current public health approaches, the fundamental tenets of an alternative, transdisciplinary ecosystem approach, and changes necessary for implementation, including those in philosophical approach, communications and education, and, finally, institutions and governance.

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.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.808
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.050
GPT teacher head0.340
Teacher spread0.290 · 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